# kb

id: replication-crisis-20260505-5
file: data/en.wikipedia.org/wiki/Replication_crisis-5.md
category: reference
title: Replication crisis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Replication_crisis
date_saved: 2026-05-05T03:45:08.741659+00:00
instance: kb-cron
parent: replication-crisis-20260505-0
summary:
Academic "publish or perish" culture exacerbates publication bias. Intense pressure to publish in recognized journals, driven by hypercompetitive environments and bibliometric career evaluations, incentivizes researchers to prioritize publishable results over validity. According to Fanelli, this pushes scientists to employ a number of strategies aimed at making results "publishable". In the context of publication bias, this can mean adopting behaviors aimed at making results positive or statistically significant, often at the expense of their validity. According to Center for Open Science founder Brian Nosek and his colleagues, "publish or perish" culture created a situation whereby the goals and values of single scientists (e.g., publishability) are not aligned with the general goals of science (e.g., pursuing scientific truth). This is detrimental to the validity of published findings. Philosopher Brian D. Earp and psychologist Jim A. C. Everett argue that, although replication is in the best interests of academics and researchers as a group, features of academic psychological culture discourage replication by individual researchers. They argue that performing replications can be time-consuming, and take away resources from projects that reflect the researcher's original thinking. They are harder to publish, largely because they are unoriginal, and even when they can be published they are


id: replication-crisis-20260505-6
file: data/en.wikipedia.org/wiki/Replication_crisis-6.md
category: reference
title: Replication crisis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Replication_crisis
date_saved: 2026-05-05T03:45:08.741659+00:00
instance: kb-cron
parent: replication-crisis-20260505-0
summary:
==== In medicine ==== Irreproducible medical studies commonly share these characteristics: investigators not being blinded to the experimental versus the control arms; failure to repeat experiments; lack of positive and negative controls; failing to report all the data; inappropriate use of statistical tests; and use of reagents that were not appropriately validated. ==== In AI research ==== In machine learning research, a range of questionable practices have emerged due to intense pressure to achieve state-of-the-art benchmark results. Common evaluation questionable practices include "benchmark overfitting" by repeatedly tuning hyperparameters on held-out test sets, selectively reporting the best of multiple random seeds or experimental runs, and "metric hacking" through unreported post hoc decisions such as choice of tokenization or evaluation scripts that inflate scores. Researchers also frequently cherry-pick tasks or datasets where their proposed model outperforms baselines, omit negative or lower-performing results, and obscure compute budgets to present energy-intensive methods as efficient. Such practices can give a misleading impression of model progress and hinder fair comparisons across methods. Moreover, many machine learning studies suffer from irreproducible research practices that impede replication and auditing. Key issues include incomplete disclosure of training details—such as dataset preprocessing, exact model hyperparameters, random seeds, and hardware configurations—and


id: replication-crisis-20260505-7
file: data/en.wikipedia.org/wiki/Replication_crisis-7.md
category: reference
title: Replication crisis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Replication_crisis
date_saved: 2026-05-05T03:45:08.741659+00:00
instance: kb-cron
parent: replication-crisis-20260505-0
summary:
=== Statistical issues === ==== Low statistical power ==== Low statistical power hinders replication for three reasons: (1) low-power replications have reduced ability to detect true effects, (2) low-power original studies produce biased effect size estimates leading to undersized replications, and (3) low-power original studies yield results unlikely to reflect true effects. Mathematically, the probability of replicating a previous publication that rejected a null hypothesis H 0 {\displaystyle H_{0}} in favor of an alternative H 1 {\displaystyle H_{1}} is ( significance ) P r ( H 0 | publication ) + ( power ) P r ( H 1 | publication ) ≤ ( power ) {\displaystyle ({\text{significance}})Pr(H_{0}|{\text{publication}})+({\text{power}})Pr(H_{1}|{\text{publication}})\leq ({\text{power}})} assuming significance is less than power. Thus, low power implies low probability of replication, regardless of how the previous publication was designed, and regardless of which hypothesis is really true. Stanley and colleagues estimated the average statistical power of psychological literature by analyzing data from 200 meta-analyses. They found that on average, psychology studies have between 33.1% and 36.4% statistical power. These values are quite low compared to the 80% considered adequate statistical power for an experiment. Across the 200 meta-analyses, the median of studies with adequate statistical power was between


id: replication-crisis-20260505-8
file: data/en.wikipedia.org/wiki/Replication_crisis-8.md
category: reference
title: Replication crisis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Replication_crisis
date_saved: 2026-05-05T03:45:08.741659+00:00
instance: kb-cron
parent: replication-crisis-20260505-0
summary:
Various statistical methods can be applied to make the p-value appear smaller than it really is. This need not be malicious, as moderately flexible data analysis, routine in research, can increase the false-positive rate to above 60%. For example, if one collects some data, applies several different significance tests to it, and publishes only the one that happens to have a p-value less than 0.05, then the total p-value for "at least one significance test reaches p < 0.05" can be much larger than 0.05, because even if the null hypothesis were true, the probability that one out of many significance tests is extreme is not itself extreme. Typically, a statistical study has multiple steps, with several choices at each step, such as during data collection, outlier rejection, choice of test statistic, choice of one-tailed or two-tailed test, etc. These choices in the "garden of forking paths" multiply, creating many "researcher degrees of freedom". The effect is similar to the file-drawer problem, as the paths not taken are not published. Consider a simple illustration. Suppose the null hypothesis is true, and we have 20 possible significance tests to apply to the dataset. Also suppose the outcomes to the significance tests


id: replication-crisis-20260505-9
file: data/en.wikipedia.org/wiki/Replication_crisis-9.md
category: reference
title: Replication crisis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Replication_crisis
date_saved: 2026-05-05T03:45:08.741659+00:00
instance: kb-cron
parent: replication-crisis-20260505-0
summary:
==== Statistical heterogeneity ==== As also reported by Stanley and colleagues, a further reason studies might fail to replicate is high heterogeneity of the to-be-replicated effects. Heterogeneity (variance in research findings due to multiple true effect sizes rather than one) is measured by the I-squared statistic, which quantifies unexplained variation in effect sizes across studies. This variation can be due to differences in experimental methods, populations, cohorts, and statistical methods between replication studies. Heterogeneity poses a challenge to studies attempting to replicate previously found effect sizes. When heterogeneity is high, subsequent replications have a high probability of finding an effect size radically different than that of the original study. Importantly, significant levels of heterogeneity are also found in direct/exact replications of a study. Stanley and colleagues discuss this while reporting a study by quantitative behavioral scientist Richard Klein and colleagues, where the authors attempted to replicate 15 psychological effects across 36 different sites in Europe and the U.S. In the study, Klein and colleagues found significant amounts of heterogeneity in 8 out of 16 effects (I-squared = 23% to 91%). Importantly, while the replication sites intentionally differed on a variety of characteristics, such differences could account for very little heterogeneity


id: replication-crisis-20260505-10
file: data/en.wikipedia.org/wiki/Replication_crisis-10.md
category: reference
title: Replication crisis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Replication_crisis
date_saved: 2026-05-05T03:45:08.741659+00:00
instance: kb-cron
parent: replication-crisis-20260505-0
summary:
and the probability of replicating the statistical study is P r ( replication | find H 1 ) = P r ( find H 1 | H 1 ) P r ( H 1 | find H 1 ) + P r ( find H 1 | H 0 ) P r ( H 0 | find H 1 ) {\displaystyle Pr({\text{replication}}|{\text{ find }}H_{1})=Pr({\text{find }}H_{1}|H_{1})Pr(H_{1}|{\text{ find }}H_{1})+Pr({\text{find }}H_{1}|H_{0})Pr(H_{0}|{\text{ find }}H_{1})} which is also different from P r ( H 1 | find H 1 ) {\displaystyle Pr(H_{1}|{\text{ find }}H_{1})} . In particular, for a fixed level of significance, the probability of replication increases with power, and prior probability for H 1 {\displaystyle H_{1}} . If the prior probability for H 1 {\displaystyle H_{1}} is small, then one would require a high power for replication. For example, if the prior probability of the null hypothesis is P r ( H 0 ) = 0.9 {\displaystyle Pr(H_{0})=0.9} , and the study found a positive result, then the posterior probability for H 1 {\displaystyle H_{1}} is P r ( H 1 | find H 1 ) = 0.50 {\displaystyle Pr(H_{1}|{\text{ find }}H_{1})=0.50} , and the replication probability is P r ( replication |


id: replication-crisis-20260505-11
file: data/en.wikipedia.org/wiki/Replication_crisis-11.md
category: reference
title: Replication crisis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Replication_crisis
date_saved: 2026-05-05T03:45:08.741659+00:00
instance: kb-cron
parent: replication-crisis-20260505-0
summary:
== Consequences == When effects are wrongly stated as relevant in the literature, failure to detect this by replication will lead to the canonization of such false facts. A 2021 study found that papers in leading general interest, psychology and economics journals with findings that could not be replicated tend to be cited more over time than reproducible research papers, likely because these results are surprising or interesting. The trend is not affected by publication of failed reproductions, after which only 12% of papers that cite the original research will mention the failed replication. Further, experts are able to predict which studies will be replicable, leading the authors of the 2021 study, Marta Serra-Garcia and Uri Gneezy, to conclude that experts apply lower standards to interesting results when deciding whether to publish them. === Public awareness and perceptions === Concerns have been expressed within the scientific community that the general public may consider science less credible due to failed replications. Research supporting this concern is sparse, but a nationally representative survey in Germany showed that more than 75% of Germans have not heard of replication failures in science. The study also found that most Germans have positive perceptions of replication


id: replication-crisis-20260505-12
file: data/en.wikipedia.org/wiki/Replication_crisis-12.md
category: reference
title: Replication crisis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Replication_crisis
date_saved: 2026-05-05T03:45:08.741659+00:00
instance: kb-cron
parent: replication-crisis-20260505-0
summary:
In response to concerns in psychology about publication bias and data dredging, more than 140 psychology journals have adopted result-blind peer review. In this approach, studies are accepted not on the basis of their findings and after the studies are completed, but before they are conducted and on the basis of the methodological rigor of their experimental designs, and the theoretical justifications for their statistical analysis techniques before data collection or analysis is done. Early analysis of this procedure has estimated that 61% of result-blind studies have led to null results, in contrast to an estimated 5% to 20% in earlier research. In addition, large-scale collaborations between researchers working in multiple labs in different countries that regularly make their data openly available for different researchers to assess have become much more common in psychology. ==== Pre-registration of studies ==== Scientific publishing has begun using pre-registration reports to address the replication crisis. The registered report format requires authors to submit a description of the study methods and analyses prior to data collection. Once the method and analysis plan is vetted through peer-review, publication of the findings is provisionally guaranteed, based on whether the authors follow the proposed protocol. One goal of


id: replication-crisis-20260505-13
file: data/en.wikipedia.org/wiki/Replication_crisis-13.md
category: reference
title: Replication crisis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Replication_crisis
date_saved: 2026-05-05T03:45:08.741659+00:00
instance: kb-cron
parent: replication-crisis-20260505-0
summary:
==== Cross-validation ==== One common statistical problem is overfitting, that is, when researchers fit a regression model over a large number of variables but a small number of data points. For example, a typical fMRI study of emotion, personality, and social cognition has fewer than 100 subjects, but each subject has 10,000 voxels. The study would fit a sparse linear regression model that uses the voxels to predict a variable of interest, such as self-reported stress. But the study would then report on the p-value of the model on the same data it was fitted to. The standard approach in statistics, where data is split into a training and a validation set, is resisted because test subjects are expensive to acquire. One possible solution is cross-validation, which allows model validation while also allowing the whole dataset to be used for model-fitting. === Replication efforts === ==== Funding ==== In July 2016, the Netherlands Organisation for Scientific Research made €3 million available for replication studies. The funding is for replication based on reanalysis of existing data and replication by collecting and analysing new data. Funding is available in the areas of social sciences, health research and healthcare innovation. In 2013, the


id: replication-crisis-20260505-14
file: data/en.wikipedia.org/wiki/Replication_crisis-14.md
category: reference
title: Replication crisis
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Replication_crisis
date_saved: 2026-05-05T03:45:08.741659+00:00
instance: kb-cron
parent: replication-crisis-20260505-0
summary:
The dominant scientific and statistical model of causation is the linear model. The linear model assumes that mental variables are stable properties which are independent of each other. In other words, these variables are not expected to influence each other. Instead, the model assumes that the variables will have an independent, linear effect on observable outcomes. Social scientists Sebastian Wallot and Damian Kelty-Stephen argue that the linear model is not always appropriate. An alternative is the complex system model which assumes that mental variables are interdependent. These variables are not assumed to be stable, rather they will interact and adapt to each specific context. They argue that the complex system model is often more appropriate in psychology, and that the use of the linear model when the complex system model is more appropriate will result in failed replications. ...psychology may be hoping for replications in the very measurements and under the very conditions where a growing body of psychological evidence explicitly discourages predicting replication. Failures to replicate may be plainly baked into the potentially incomplete, but broadly sweeping failure of human behavior to conform to the standard of independen[ce] ... ==== Replication should seek to revise theories ==== Replication is


id: reproducibility-20260505-0
file: data/en.wikipedia.org/wiki/Reproducibility-0.md
category: reference
title: Reproducibility
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Reproducibility
date_saved: 2026-05-05T03:45:09.848006+00:00
instance: kb-cron
parent: reproducibility-20260505-0
summary:
Reproducibility, closely related to replicability and repeatability, is a major principle underpinning the scientific method. For the findings of a study to be reproducible means that results obtained by an experiment or an observational study or in a statistical analysis of a data set should be achieved again with a high degree of reliability when the study is replicated. There are different kinds of replication but typically replication studies involve different researchers using the same methodology. Only after one or several such successful replications should a result be recognized as scientific knowledge. == History == The first to stress the importance of reproducibility in science was the Anglo-Irish chemist Robert Boyle, in England in the 17th century. Boyle's air pump was designed to generate and study vacuum, which at the time was a very controversial concept. Indeed, distinguished philosophers such as René Descartes and Thomas Hobbes denied the very possibility of vacuum existence. Historians of science Steven Shapin and Simon Schaffer, in their 1985 book Leviathan and the Air-Pump, describe the debate between Boyle and Hobbes, ostensibly over the nature of vacuum, as fundamentally an argument about how useful knowledge should be gained. Boyle, a pioneer of the experimental method,


id: reproducibility-20260505-1
file: data/en.wikipedia.org/wiki/Reproducibility-1.md
category: reference
title: Reproducibility
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Reproducibility
date_saved: 2026-05-05T03:45:09.848006+00:00
instance: kb-cron
parent: reproducibility-20260505-0
summary:
=== Reproducible research method === The term reproducible research refers to the idea that scientific results should be documented in such a way that their deduction is fully transparent. This requires a detailed description of the methods used to obtain the data and making the full dataset and the code to calculate the results easily accessible. This is the essential part of open science. To make any research project computationally reproducible, general practice involves all data and files being clearly separated, labelled, and documented. All operations should be fully documented and automated as much as practicable, avoiding manual intervention where feasible. The workflow should be designed as a sequence of smaller steps that are combined so that the intermediate outputs from one step directly feed as inputs into the next step. Version control should be used as it lets the history of the project be easily reviewed and allows for the documenting and tracking of changes in a transparent manner. A basic workflow for reproducible research involves data acquisition, data processing and data analysis. Data acquisition primarily consists of obtaining primary data from a primary source such as surveys, field observations, experimental research, or obtaining data from an existing source.


id: reproducibility-20260505-2
file: data/en.wikipedia.org/wiki/Reproducibility-2.md
category: reference
title: Reproducibility
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Reproducibility
date_saved: 2026-05-05T03:45:09.848006+00:00
instance: kb-cron
parent: reproducibility-20260505-0
summary:
== Noteworthy irreproducible results == Hideyo Noguchi became famous for correctly identifying the bacterial agent of syphilis, but also claimed that he could culture this agent in his laboratory. Nobody else has been able to produce this latter result. In March 1989, University of Utah chemists Stanley Pons and Martin Fleischmann reported the production of excess heat that could only be explained by a nuclear process ("cold fusion"). The report was astounding given the simplicity of the equipment: it was essentially an electrolysis cell containing heavy water and a palladium cathode which rapidly absorbed the deuterium produced during electrolysis. The news media reported on the experiments widely, and it was a front-page item on many newspapers around the world (see science by press conference). Over the next several months others tried to replicate the experiment, but were unsuccessful. Nikola Tesla claimed as early as 1899 to have used a high frequency current to light gas-filled lamps from over 25 miles (40 km) away without using wires. In 1904 he built Wardenclyffe Tower on Long Island to demonstrate means to send and receive power without connecting wires. The facility was never fully operational and was not completed due to economic problems,


id: reproducibility-project-20260505-0
file: data/en.wikipedia.org/wiki/Reproducibility_Project-0.md
category: reference
title: Reproducibility Project
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Reproducibility_Project
date_saved: 2026-05-05T03:45:10.989762+00:00
instance: kb-cron
parent: reproducibility-project-20260505-0
summary:
The Reproducibility Project is a series of crowdsourced collaborations aiming to reproduce published scientific studies, finding high rates of results which could not be replicated. It has resulted in two major initiatives focusing on the fields of psychology and cancer biology. The project has brought attention to the replication crisis, and has contributed to shifts in scientific culture and publishing practices to address it. The project was led by the Center for Open Science and its co-founder, Brian Nosek, who started the project in November 2011. == Results == Brian Nosek of University of Virginia and colleagues sought out to replicate 100 different studies, all published in 2008. The project pulled these studies from three different journals, Psychological Science, the Journal of Personality and Social Psychology, and the Journal of Experimental Psychology: Learning, Memory, and Cognition, published in 2008 to see if they could get the same results as the initial findings. 97 of the original studies had significant effects, but of those 97, only 36% of the replications yielded significant findings (p value below 0.05), and the effects were often smaller than those in the original papers. The authors emphasized that the findings reflect a problem that affects all


id: research-20260505-0
file: data/en.wikipedia.org/wiki/Research-0.md
category: reference
title: Research
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research
date_saved: 2026-05-05T03:45:12.257936+00:00
instance: kb-cron
parent: research-20260505-0
summary:
Research is creative and systematic work undertaken to increase the stock of knowledge. It involves the collection, organization, and analysis of evidence to increase understanding of a topic, characterized by a particular attentiveness to controlling sources of bias and error. These activities are characterized by accounting and controlling for biases. A research project may be an expansion of past work in the field. To test the validity of instruments, procedures, or experiments, research may replicate elements of prior projects or the project as a whole. The primary purposes of basic research (as opposed to applied research) are documentation, discovery, interpretation, and the research and development (R&D) of methods and systems for the advancement of human knowledge. Approaches to research depend on epistemologies, which vary considerably both within and between humanities and sciences. There are several forms of research: scientific, humanities, artistic, economic, social, business, marketing, practitioner research, life, technological, etc. The scientific study of research practices is known as meta-research. A researcher is a person who conducts research. == Etymology == The word research is derived from the Middle French "recherche", which means "to go about seeking", the term itself being derived from the Old French term "recerchier", a compound


id: research-20260505-1
file: data/en.wikipedia.org/wiki/Research-1.md
category: reference
title: Research
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research
date_saved: 2026-05-05T03:45:12.257936+00:00
instance: kb-cron
parent: research-20260505-0
summary:
=== Artistic research === Artistic research, also seen as 'practice-based research', can take form when creative works are considered both the research and the object of research itself. It is the debatable body of thought which offers an alternative to purely scientific methods in research in its search for knowledge and truth. The controversial trend of artistic teaching becoming more academics-oriented is leading to artistic research being accepted as the primary mode of enquiry in art as in the case of other disciplines. One of the characteristics of artistic research is that it must accept subjectivity as opposed to the classical scientific methods. As such, it is similar to the social sciences in using qualitative research and intersubjectivity as tools to apply measurement and critical analysis. Artistic research has been defined by the School of Dance and Circus (Dans och Cirkushögskolan, DOCH), Stockholm in the following manner – "Artistic research is to investigate and test with the purpose of gaining knowledge within and for our artistic disciplines. It is based on artistic practices, methods, and criticality. Through presented documentation, the insights gained shall be placed in a context." Artistic research aims to enhance knowledge and understanding with presentation of the


id: research-20260505-2
file: data/en.wikipedia.org/wiki/Research-2.md
category: reference
title: Research
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research
date_saved: 2026-05-05T03:45:12.257936+00:00
instance: kb-cron
parent: research-20260505-0
summary:
Identification of research problem Literature review Specifying the purpose of research Determining specific research questions Specification of a conceptual framework, sometimes including a set of hypotheses Choice of a methodology (for data collection) Data collection Verifying data Analyzing and interpreting the data Reporting and evaluating research Communicating the research findings and, possibly, recommendations The steps generally represent the overall process; however, they should be viewed as an ever-changing iterative process rather than a fixed set of steps. Most research begins with a general statement of the problem, or rather, the purpose for engaging in the study. The literature review identifies flaws or holes in previous research which provides justification for the study. Often, a literature review is conducted in a given subject area before a research question is identified. A gap in the current literature, as identified by a researcher, then engenders a research question. The research question may be parallel to the hypothesis. The hypothesis is the supposition to be tested. The researcher(s) collects data to test the hypothesis. The researcher(s) then analyzes and interprets the data via a variety of statistical methods, engaging in what is known as empirical research. The results of the data analysis in rejecting


id: research-20260505-3
file: data/en.wikipedia.org/wiki/Research-3.md
category: reference
title: Research
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research
date_saved: 2026-05-05T03:45:12.257936+00:00
instance: kb-cron
parent: research-20260505-0
summary:
Exploratory research, which helps to identify and define a problem or question. Constructive research, which tests theories and proposes solutions to a problem or question. Empirical research, which tests the feasibility of a solution using empirical evidence. There are two major types of empirical research design: qualitative research and quantitative research. Researchers choose qualitative or quantitative methods according to the nature of the research topic they want to investigate and the research questions they aim to answer: Qualitative research Qualitative research refers to much more subjective non-quantitative, use different methods of collecting data, analyzing data, interpreting data for meanings, definitions, characteristics, symbols metaphors of things. Qualitative research further classified into the following types: Ethnography: This research mainly focus on culture of group of people which includes share attributes, language, practices, structure, value, norms and material things, evaluate human lifestyle. Ethno: people, Grapho: to write, this disciple may include ethnic groups, ethno genesis, composition, resettlement and social welfare characteristics. Phenomenology: It is very powerful strategy for demonstrating methodology to health professions education as well as best suited for exploring challenging problems in health professions educations. In addition, PMP researcher Mandy Sha argued that a project management approach is necessary to control


id: research-20260505-4
file: data/en.wikipedia.org/wiki/Research-4.md
category: reference
title: Research
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research
date_saved: 2026-05-05T03:45:12.257936+00:00
instance: kb-cron
parent: research-20260505-0
summary:
In many disciplines, Western methods of conducting research are predominant. Researchers are overwhelmingly taught Western methods of data collection and study. The increasing participation of indigenous peoples as researchers has brought increased attention to the scientific lacuna in culturally sensitive methods of data collection. Western methods of data collection may not be the most accurate or relevant for research on non-Western societies. For example, "Hua Oranga" was created as a criterion for psychological evaluation in Māori populations, and is based on dimensions of mental health important to the Māori people – "taha wairua (the spiritual dimension), taha hinengaro (the mental dimension), taha tinana (the physical dimension), and taha whanau (the family dimension)". Even though Western dominance seems to be prominent in research, some scholars, such as Simon Marginson, argue for "the need [for] a plural university world". Marginson argues that the East Asian Confucian model could take over the Western model. This could be due to changes in funding for research both in the East and the West. Focused on emphasizing educational achievement, East Asian cultures, mainly in China and South Korea, have encouraged the increase of funding for research expansion. In contrast, in the Western academic world, notably in


id: research-20260505-5
file: data/en.wikipedia.org/wiki/Research-5.md
category: reference
title: Research
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research
date_saved: 2026-05-05T03:45:12.257936+00:00
instance: kb-cron
parent: research-20260505-0
summary:
Academic publishing is a system that is necessary for academic scholars to peer review the work and make it available for a wider audience. The system varies widely by field and is also always changing, if often slowly. Most academic work is published in journal article or book form. There is also a large body of research that exists in either a thesis or dissertation form. These forms of research can be found in databases explicitly for theses and dissertations. In publishing, STM publishing is an abbreviation for academic publications in science, technology, and medicine. Most established academic fields have their own scientific journals and other outlets for publication, though many academic journals are somewhat interdisciplinary, and publish work from several distinct fields or subfields. The kinds of publications that are accepted as contributions of knowledge or research vary greatly between fields, from the print to the electronic format. A study suggests that researchers should not give great consideration to findings that are not replicated frequently. It has also been suggested that all published studies should be subjected to some measure for assessing the validity or reliability of its procedures to prevent the publication of unproven findings. Business models are


id: research-ethics-20260505-0
file: data/en.wikipedia.org/wiki/Research_ethics-0.md
category: reference
title: Research ethics
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research_ethics
date_saved: 2026-05-05T03:45:13.584991+00:00
instance: kb-cron
parent: research-ethics-20260505-0
summary:
Research ethics is a discipline within the study of applied ethics. Its scope ranges from general scientific integrity and misconduct to the treatment of human and animal subjects. The social responsibilities of scientists and researchers are not traditionally included and are less well defined. The discipline is most developed in medical research. Beyond the issues of falsification, fabrication, and plagiarism that arise in every scientific field, research design in human subject research and animal testing are the areas that raise ethical questions most often. The list of historic cases includes many large-scale violations and crimes against humanity such as Nazi human experimentation and the Tuskegee syphilis experiment which led to international codes of research ethics. No approach has been universally accepted, but typically cited codes are the 1947 Nuremberg Code, the 1964 Declaration of Helsinki, and the 1978 Belmont Report. Today, research ethics committees, such as those of the US, UK, and EU, govern and oversee the responsible conduct of research. One major goal being to reduce questionable research practices. Research in other fields such as social sciences, information technology, biotechnology, or engineering may generate ethical concerns. == History == The list of historic cases includes many large scale violations


id: research-transparency-20260505-0
file: data/en.wikipedia.org/wiki/Research_transparency-0.md
category: reference
title: Research transparency
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research_transparency
date_saved: 2026-05-05T03:45:14.744472+00:00
instance: kb-cron
parent: research-transparency-20260505-0
summary:
Research transparency is a major aspect of scientific research. It covers a variety of scientific principles and practices: reproducibility, data and code sharing, citation standards or verifiability. The definitions and norms of research transparency significantly differ depending on the disciplines and fields of research. Due to the lack of consistent terminology, research transparency has frequently been defined negatively by addressing non-transparent usages (which are part of questionable research practices). After 2010, recurrent issues of research methodology have been increasingly acknowledged as structural crisis, that involve deep changes at all stages of the research process. Transparency has become a key value of the open science movement, which evolved from an initial focus on publishing to encompass a large diversity of research outputs. New common standards for research transparency, like the TOP Guidelines, aims to build and strengthen open research culture across disciplines and epistemic cultures. == Definitions == === Confused terminologies === There is no widespread consensus on the definition of research transparency. Differences between disciplines and epistemic cultures has largely contributed to different acceptions. The reproduction of past research has been a leading source of dissent. In an experimental setting, reproduction relies on the same set-up and apparatus, while replication


id: research-transparency-20260505-1
file: data/en.wikipedia.org/wiki/Research_transparency-1.md
category: reference
title: Research transparency
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research_transparency
date_saved: 2026-05-05T03:45:14.744472+00:00
instance: kb-cron
parent: research-transparency-20260505-0
summary:
=== A new dimension of open science? === Transparency has been increasingly acknowledged as an important component of open science. Until the 2010s, definitions of open science have been mostly focused on technical access and enhanced participation and collaboration between academics and non-academics. In 2016, Liz Lyon identified transparency as a "third dimension" of open science, due to the fact that "the concept of transparency and the associated term 'reproducibility', have become increasingly important in the current interdisciplinary research environment." According to Kevin Elliott, the open science movement "encompasses a number of different initiatives aimed at somewhat different forms of transparency." First drafted in 2014, the TOP guidelines have significantly contributed to bring transparency on the agenda of the open science movements. They aim to promote an "open research culture" and implement "strong incentives to be more transparent". They rely on eight standards, with different levels of compliance. While the standards are modular, they also aim to articulate a consistent ethos of science as "they also complement each other, in that commitment to one standard may facilitate adoption of others.". This open science framework of transparency has been in turn coopted by leading contributors and institutions on the topic of


id: research-transparency-20260505-2
file: data/en.wikipedia.org/wiki/Research_transparency-2.md
category: reference
title: Research transparency
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research_transparency
date_saved: 2026-05-05T03:45:14.744472+00:00
instance: kb-cron
parent: research-transparency-20260505-0
summary:
=== Preconditions of the transparency crisis (1945–2000) === The development of big science after the Second World War has created unprecedented challenges for research transparency. The generalization of statistical methods across a large number of fields, as well as the increasing breadth and complexity of research projects, entailed a series of concerns about the lack of proper documentation of the scientific process. Due to the expansion of the published research output, new quantitative methods for literature surveys have been developed under the label of meta-analysis or meta-science. These rely on the assumption that quantitative results and the details of the experimental and observational framework are sound (such as the size or the composition of the sample). In 1966, Stanley Schor and Irving Karten published one of the first generic evaluation of statistical methods in 67 leading medical journals. While few outright problematic papers were found, "in almost 73% of the reports read (those needing revision and those which should have been rejected), conclusions were drawn when the justification for these conclusions was invalid" In the 1970s and the 1980s, scientific misconducts gradually ceased to be presented as individual misconducts and became collective problems that need to be addressed by scientific


id: research-transparency-20260505-3
file: data/en.wikipedia.org/wiki/Research_transparency-3.md
category: reference
title: Research transparency
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research_transparency
date_saved: 2026-05-05T03:45:14.744472+00:00
instance: kb-cron
parent: research-transparency-20260505-0
summary:
=== Research transparency and open science (2015–) === Since 2000, the open science movement has expanded beyond access to scientific outputs (publication, data or software) to encompass the entire process of scientific production. In 2018, Vicente-Saez and Martinez-Fuentes have attempted to map the common values shared by the standard definitions of open science in the English-speaking scientific literature indexed on Scopus and the Web of Science. Access is no longer the main dimension of open science, as it has been extended by more recent commitments toward transparency, collaborative work and social impact. Through this process, open science has been increasingly structured over a consisting set of ethical principles: "novel open science practices have developed in tandem with novel organising forms of conducting and sharing research through open repositories, open physical labs, and transdisciplinary research platforms. Together, these novel practices and organising forms are expanding the ethos of science at universities." The global scale of the open science movement and its integration in a large variety of technical tools, standards and regulations makes it possible to overcome the "classic collective action problem" embodied by research transparency: there is a structural discrepancy between the stated objective of scientific institutions and the lack


id: research-transparency-20260505-4
file: data/en.wikipedia.org/wiki/Research_transparency-4.md
category: reference
title: Research transparency
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research_transparency
date_saved: 2026-05-05T03:45:14.744472+00:00
instance: kb-cron
parent: research-transparency-20260505-0
summary:
==== Result reproducibility ==== Goodman, Fanelli and Ioannidis define result reproducibility as "obtaining the same results from the conduct of an independent study whose procedures are as closely matched". Result reproducibility is comparable to replication in an experimental context and reproducibility in a computational context. The definition of replicability retained in the National Academies of Science, largely applies to it: "obtaining consistent results across studies aimed at answering the same scientific question, each of which has obtained its own data.". The reproducibility crisis met in experimental disciplines like psychology or medicine is mostly a crisis of "result reproducibility", since it concerns research that cannot been simply re-executed, but involve the independent recreation of the experimental design. As such it is arguably the most debated form of research transparency in the recent years. Result reproducibility is harder to achieve than other forms of research transparency. It involve a variety of issues that may include computational reproducibility, accuracy of scientific measurement and diversity of methodological approaches. There are no universal standard to determine how close are the original procedures matched and criterium may vary depending on the disciplines or, even on the field of research. Consequently, meta-analysis of reproducibility have faced significant


id: research-transparency-20260505-5
file: data/en.wikipedia.org/wiki/Research_transparency-5.md
category: reference
title: Research transparency
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Research_transparency
date_saved: 2026-05-05T03:45:14.744472+00:00
instance: kb-cron
parent: research-transparency-20260505-0
summary:
=== Sharing of research outputs === Data sharing has been early on identified as major potential solution to the reproducibility crisis and the lack of solid guidelines for statistical indicators. In 2005, John Ioannidis hypothesized that "some kind of registration or networking of data collections or investigators within fields may be more feasible than registration of each and every hypothesis-generating experiment." The sharing of research outputs is covered by three standards of the TOPs guidelines: on Data transparency (2), Analytic/code methods transparency (3) and Research materials transparency (4). All the relevant data, code and research materials are to be stored on a "trusted repository" and all analysis being already reproduced independently prior to publication. === Extended citation standards === While citation standards are commonly applied to academic reference, there is much less formalization for all the other research output, such as data, code, primary sources or qualitative assessments. In 2012, the American Political Science Association adopted new policies for open qualitative research. They covered three dimensions of transparency: data transparency (in the sense of precise bibliographic data to the original sources), analytic transparency (in regards to claims extrapolated from the cited sources) and production transparency (in reference to the editorial


id: retrodiction-20260505-0
file: data/en.wikipedia.org/wiki/Retrodiction-0.md
category: reference
title: Retrodiction
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Retrodiction
date_saved: 2026-05-05T03:45:16.005780+00:00
instance: kb-cron
parent: retrodiction-20260505-0
summary:
Retrodiction is the act of making a prediction about the past. It is also known as postdiction (but this should not be confused with the use of the term in criticisms of parapsychological research). == Activity == The activity of retrodiction (or postdiction) involves moving backwards in time, step-by-step, in as many stages as are considered necessary, from the present into the speculated past to establish the ultimate cause of a specific event (for instance, in the case of reverse engineering, forensics, etc.). Given that retrodiction is a process in which "past observations, events and data are used as evidence to infer the process(es) that produced them" and that diagnosis "involve[s] going from visible effects such as symptoms, signs and the like to their prior causes", the essential balance between prediction and retrodiction could be characterized as: retrodiction : diagnosis :: prediction : prognosis regardless of whether the prognosis is of the course of the disease in the absence of treatment, or of the application of a specific treatment regimen to a specific disorder in a particular patient: "We consider diagnostic inference to be based on causal thinking, although in doing diagnosis one has to mentally reverse the time order


id: role-of-chance-in-scientific-discoveries-20260505-0
file: data/en.wikipedia.org/wiki/Role_of_chance_in_scientific_discoveries-0.md
category: reference
title: Role of chance in scientific discoveries
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Role_of_chance_in_scientific_discoveries
date_saved: 2026-05-05T03:45:17.281687+00:00
instance: kb-cron
parent: role-of-chance-in-scientific-discoveries-20260505-0
summary:
The role of chance, or "luck", in science comprises all ways in which unexpected discoveries are made. Many domains, especially psychology, are concerned with the way science interacts with chance –particularly "serendipity" (accidents that, through sagacity, are transformed into opportunity). Psychologist Kevin Dunbar and colleagues estimate that between 30% and 50% of all scientific discoveries are accidental in some sense (see examples below). Scientists themselves in the 19th and 20th century acknowledged the role of fortunate luck or serendipity in discoveries. Psychologist Alan A. Baumeister says a scientist must be "sagacious" (attentive and clever) to benefit from an accident. Dunbar quotes Louis Pasteur's saying that "Chance favors only the prepared mind". The prepared mind, Dunbar suggests, is one trained for observational rigor. Dunbar adds that there is a great deal of writing about the role that serendipity ("happy accidents") plays in the scientific method. Research suggests that scientists are taught various heuristics and practices that allow their investigations to benefit, and not suffer, from accidents. First, careful control conditions allow scientists to properly identify something as "unexpected". Once a finding is recognized as legitimately unexpected and in need of explaining, researchers can attempt to explain it: They work across various


id: royal-commission-on-animal-magnetism-20260505-0
file: data/en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism-0.md
category: reference
title: Royal Commission on Animal Magnetism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism
date_saved: 2026-05-05T03:45:20.529918+00:00
instance: kb-cron
parent: royal-commission-on-animal-magnetism-20260505-0
summary:
The Royal Commission on Animal Magnetism involved two entirely separate and independent French Royal Commissions, each appointed by Louis XVI in 1784, that were conducted simultaneously by a committee composed of four physicians from the Paris Faculty of Medicine (Faculté de médecine de Paris) and five scientists from the Royal Academy of Sciences (Académie des sciences) (the "Franklin Commission", named for Benjamin Franklin), and a second committee composed of five physicians from the Royal Society of Medicine (Société Royale de Médecine) (the "Society Commission"). Each Commission took five months to complete its investigations. The "Franklin" Report was presented to the King on 11 August 1784 – and was immediately published and very widely circulated throughout France and neighbouring countries – and the "Society" Report was presented to the King five days later on 16 August 1784. The "Franklin Commission's" investigations are notable as a very early "classic" example of a systematic controlled trial, which not only applied "sham" and "genuine" procedures to patients with "sham" and "genuine" disorders, but, significantly, was the first to use the "blindfolding" of both the investigators and their subjects. The report of the ["Franklin"] Royal Commission of 1784 ... is a masterpiece of its genre,


id: royal-commission-on-animal-magnetism-20260505-1
file: data/en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism-1.md
category: reference
title: Royal Commission on Animal Magnetism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism
date_saved: 2026-05-05T03:45:20.529918+00:00
instance: kb-cron
parent: royal-commission-on-animal-magnetism-20260505-0
summary:
From the perspective of a given phenomenon, one can look down to the entities and activities composing it. One can look up to the higher-level mechanisms of which it is a component. One can look back to the mechanisms that come before it or by which it developed. One can look forward to what comes after it. [And, finally] one can look around to see the wider context with which it operates. === Tensions within the royal family === Prior to his arrival in Paris in 1777 – with a letter of recommendation from Chancellor von Kaunitz of the Habsburg monarchy to the Austrian Ambassador to France, the Comte de Mercy-Argenteau (who, in turn, introduced Mesmer to Jean-Baptiste Le Roy (1720–1800), the Director of the Academy of Sciences) – Mesmer was already known to Marie Antoinette. At the urging of her two closest friends, Marie-Paule Angélique d’Albert de Luynes (1744–1781), "the Duchesse de Chaulnes" and Marie Thérèse Louise de Savoie-Carignan (1749–1792), "the Princess of Lamballe", both of whom "had benefited from Mesmer's treatment", Marie Antoinette had been able to arrange for both Mesmer and d'Eslon to be officially "interviewed" by (an otherwise unidentified) representative of the King on 14 March


id: royal-commission-on-animal-magnetism-20260505-2
file: data/en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism-2.md
category: reference
title: Royal Commission on Animal Magnetism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism
date_saved: 2026-05-05T03:45:20.529918+00:00
instance: kb-cron
parent: royal-commission-on-animal-magnetism-20260505-0
summary:
=== Scientific issues === In a prevailing atmosphere of "[an overall] redefinition of frontiers in the legitimacy of knowledge" – and, in relation to Mesmer's claims, a redefinition "which did not necessarily match the public popularity that they attracted" (Zanetti, 2018), p. 59) – the issue of the existence (or not) of a substantial "magnetic fluid" and/or "animal magnetism" required resolution. === Medical issues === At a time when, in relation to "healers and healing", the conglomerate of "physicians, empirics, surgeons, apothecaries, folk healers, and religious personalities all vied with each other (as well as worked together) for medical legitimacy and patients" (Broomhall, 2004, p. 5), Mesmer was not only a "foreign national", but also one that had no affiliation of any kind with any known professional medical association within France (or elsewhere in Europe); and, as a consequence, his professional conduct, his medical practice, his medico-commercial enterprises, and his therapeutic endeavours were not regulated in any way. Moreover, the efficacy of Mesmer's interventions had never been objectively tested, neither the agency nor the (pre- and post-intervention) veracity of his supposed "cures" had ever been objectively verified, and, finally, in relation to the presenting conditions of those with (supposedly) 'real'


id: royal-commission-on-animal-magnetism-20260505-3
file: data/en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism-3.md
category: reference
title: Royal Commission on Animal Magnetism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism
date_saved: 2026-05-05T03:45:20.529918+00:00
instance: kb-cron
parent: royal-commission-on-animal-magnetism-20260505-0
summary:
The second of the two Royal Commissions, usually referred to as the "Society Commission", was appointed on 5 April 1784. It was composed of five eminent physicians from the Royal Society of Medicine – the physician and one of the first members of the Royal Society, Charles-Louis-François Andry (1741–1829), the physician Claude-Antoine Caille (b. 1743), the botanist Antoine Laurent de Jussieu (1748–1836), the physician, Collège de France professor, one of the original directors of the Royal Society, and committed advocate of the therapeutic applications of electricity, Pierre Jean Claude Mauduyt de La Varenne (1732–1792), and the physician and Professor of chemistry in the Collège de France, Pierre-Isaac Poissonnier (1720–1798) – and, as Pattie remarks (1994, p. 156), "the impression given by [their] report is that the commissioners were busy practitioners who wanted to devote no more time to the project than was necessary". Although the investigations of the "Society Commission" were less thorough and less detailed than those of the "Franklin Commission" they were essentially of the same nature, and it is a matter of fact that neither Commission examined Mesmer's practices – they only examined the practices of d'Eslon. == Franz Mesmer == Franz Anton Mesmer (1734–1815), born in


id: royal-commission-on-animal-magnetism-20260505-4
file: data/en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism-4.md
category: reference
title: Royal Commission on Animal Magnetism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism
date_saved: 2026-05-05T03:45:20.529918+00:00
instance: kb-cron
parent: royal-commission-on-animal-magnetism-20260505-0
summary:
=== A concept that must not be reified === It is clear from his Mémoire (1799) that Mesmer was very aware of the human propensity – in the normal, conventional use of language (la langue de convention) – to speak of "properties" or "qualities" (i.e., these "metaphysical abstractions", illusions de la méthaphysique), as if they were "substances": in Mesmer's words, "substantivise the properties", substantisia les propriétés (Mesmer 1799, pp. 15–17). – in other words, "reification", in the manner of Whitehead's "fallacy of misplaced concreteness". Mesmer was also well aware of the extent to which, through the "distortion" caused by these "substantive words" (mot substantif) – which inappropriately "personified" (personnifia) these metaphysical abstractions (p. 16) – one is induced to believe in the actual physical existence of the "substance" itself. Given these observations, Mesmer was most emphatic in his continuous warnings that his abstract "principles" should not be "substantivised". It is significant that Mesmer (1799) describes how, once he had formulated the abstract, overarching (metaphorical) construct/concept of "animal magnetism" as the therapeutic agent (a quarter of a century earlier) – and with his hope that this newly described "principle of action" (principe de action), when considered as an agent, "could become


id: royal-commission-on-animal-magnetism-20260505-5
file: data/en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism-5.md
category: reference
title: Royal Commission on Animal Magnetism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism
date_saved: 2026-05-05T03:45:20.529918+00:00
instance: kb-cron
parent: royal-commission-on-animal-magnetism-20260505-0
summary:
=== Post-Mesmer === In late 1782, and eighteen months before the Royal Commission, d'Eslon had (acrimoniously) parted ways with Mesmer; and, despite a brief reconciliation, the relationship was terminated in late 1783. On 28 December 1783, d'Eslon wrote a letter to the Journal de Paris, which not only described the difficulties he had experienced with Mesmer, but also announced that he was opening his own (entirely independent) clinic. Following his break with Mesmer, d'Eslon not only launched his own clinical operation on his break with Mesmer, d'Eslon took all of the patients he had brought to Mesmer with him – but also began teaching his own theories and practices (i.e., rather than those of Mesmer). According to d'Eslon's own account (d'Eslon, 1784b, pp. 25–26), Mesmer had taught 300 students, 160 of whom were medical men (médecins), and d'Eslon himself had taught 160 medical men (this group included 21 members of the Paris Faculty of Medicine). Given that many of those who had privately paid Mesmer for the details of "the secret" were greatly dissatisfied, and had "[justifiably] accused [Mesmer] of having enunciated a theory which was merely a collection of obscure principles" (Binet & Féré, 1888, p. 13), it seems


id: royal-commission-on-animal-magnetism-20260505-6
file: data/en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism-6.md
category: reference
title: Royal Commission on Animal Magnetism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism
date_saved: 2026-05-05T03:45:20.529918+00:00
instance: kb-cron
parent: royal-commission-on-animal-magnetism-20260505-0
summary:
[The baquet] is a vat about six to seven feet, more or less, in diameter by eighteen inches in height. There is a double bottom in the interior of this vat, in which fragments of broken bottles, gravel, stones, and sticks of pounded sulfur and iron filings are placed. All of this is filled with water and covered up with a floor nailed into the vat. On the surface of the lid, six inches in from the rim, one makes various holes in order to allow the passage of iron rods which are arranged so that one end penetrates the bottom of the vat and the other is directed, by means of a curve, over the pit of the stomach of the patient or other affected parts of the body. Mesmer specifically stressed the primary importance of the patients' hand-holding as a factor in the "augmentation" of the force/quality of the power of the "animal magnetism". Moreover, and significantly, Mesmer (separately) acknowledged that, if it was ever to come to pass that he had a suitable "establishment" – i.e., one with sufficient space available for all the assembled patients to hold hands – he would "abolish the use of baquets"


id: royal-commission-on-animal-magnetism-20260505-7
file: data/en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism-7.md
category: reference
title: Royal Commission on Animal Magnetism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism
date_saved: 2026-05-05T03:45:20.529918+00:00
instance: kb-cron
parent: royal-commission-on-animal-magnetism-20260505-0
summary:
In his response to the Reports (d'Eslon, 1784b, pp. 21–22), d'Eslon complained that the Commissioners' emphasis on "convulsions" was not justified: among those who received group treatment during the commission's investigations (i.e., involving "50 to 60 individuals"), he wrote, there were never more than six or seven who displayed "convulsions" to any degree – and, further, of the more than 500 patients he had treated over the preceding three years, only 20 of those had manifested "convulsions" (and almost all of those had been suffering from "convulsions" before presenting for any treatment from d'Eslon). He also rejected the suggestions of any connection between the "convulsions" of epilepsy and those of the "crises", citing the cases of two of his patients, who were epileptic and "frequently had seizures at home", who never had a single "attack" during their treatment at his clinic (p. 23). Joseph Michel Antoine Servan, the one time Advocate-General to the Parlement of Grenoble, who reported (at Servan, 1784, p. 3) that, in "the Provinces" – where the various social classes were not kept apart around "the baquet", as they were in Paris – that, in relation to the concerns that the Commissioners expressed in relation to the


id: royal-commission-on-animal-magnetism-20260505-8
file: data/en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism-8.md
category: reference
title: Royal Commission on Animal Magnetism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism
date_saved: 2026-05-05T03:45:20.529918+00:00
instance: kb-cron
parent: royal-commission-on-animal-magnetism-20260505-0
summary:
=== The substantial existence of "animal magnetism" and "magnetic fluid" were investigated === Rather than being concerned with the applications, utility, and clinical efficacy of d'Eslon's "animal magnetism", the primary concern of each Commission was the significant, crucial, and exclusive question of whether or not d'Eslon's (supposed) "animal magnetic fluid" actually existed in some substantial physical way – for the simple reason that, as the two sets of Commissioners each noted in their independent reports, "Animal magnetism may well exist without being useful but it cannot be useful if it does not exist." === Mesmer's earlier refusal to have his "magnetic" interventions scrutinized === Already, in his earlier (18 September 1780) interaction with the Paris Faculty of Medicine, Mesmer had refused to have his therapeutic interventions on a set of entirely "new" patients directly scrutinized, claiming that his already-achieved "cures" were an objective matter of record. Mesmer justified his refusal as follows: Here is what I said to M. de Lassonne; however bizarre [it may seem] at first sight it is nevertheless entirely serious and very much applicable to the question. When a thief is convicted of theft he is hanged: when a murderer is convicted of murder he is


id: royal-commission-on-animal-magnetism-20260505-9
file: data/en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism-9.md
category: reference
title: Royal Commission on Animal Magnetism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism
date_saved: 2026-05-05T03:45:20.529918+00:00
instance: kb-cron
parent: royal-commission-on-animal-magnetism-20260505-0
summary:
it was [their] duty ... to confine themselves to arguments purely physical, that is, to the momentaneous [sic] effects of the fluid upon the animal frame, excluding from these effects all the illusions which might mix with them, and assuring themselves that they could proceed from no other cause than the animal magnetism." === Problems with objectively determining the precise therapeutic action of any supposed "efficacious remedy" === In support of its decision, the "Franklin Commission" produced a cogent, extended argument, consistent with the medical knowledge of the day, that is equally relevant to similar investigations in the present day: The majority of diseases have their seat in the interior part of our frame. The collective experience of a great number of centuries has made us acquainted with the symptoms, which indicate and discriminate them; the same experience has taught the method in which they are to be treated. What is the object of the efforts of the physician in this method? It is not to oppose and to subdue nature, it is to assist her in her operations. Nature, says the father of the medical science [viz., Hippocrates], cures the diseased; but sometimes she encounters obstacles, which constrain her


id: royal-commission-on-animal-magnetism-20260505-10
file: data/en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism-10.md
category: reference
title: Royal Commission on Animal Magnetism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism
date_saved: 2026-05-05T03:45:20.529918+00:00
instance: kb-cron
parent: royal-commission-on-animal-magnetism-20260505-0
summary:
They saw in the centre of a large apartment a circular box, made of oak, and about a foot or a foot and an [sic] half deep, which is called the bucket [baquet]; the lid of this box is pierced with a number of holes, in which are inserted branches of iron, elbowed and moveable. The patients are arranged in ranks about this [baquet], and each has his branch of iron, which by means of the elbow may be applied immediately to the part affected; a cord passed round their bodies connects them one with the other: sometimes a second means of communication is introduced, by the insertion of the thumb of each patient between the forefinger and thumb of the patient next him; the thumb thus inserted is pressed by the person holding it; the impression received by the left hand of the patient, communicates through his right, and thus passes through the whole circle.A piano forté is placed in one corner of the apartment, and different airs are played with various degrees of rapidity; vocal music is sometimes added to the instrumental.The persons who superintend the process, have each of them an iron rod in his hand, from


id: royal-commission-on-animal-magnetism-20260505-11
file: data/en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism-11.md
category: reference
title: Royal Commission on Animal Magnetism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism
date_saved: 2026-05-05T03:45:20.529918+00:00
instance: kb-cron
parent: royal-commission-on-animal-magnetism-20260505-0
summary:
==== Immediate publication and dissemination ==== The report was immediately published by the government printer; and at least 20,000 copies were rapidly and very widely circulated throughout France and neighbouring countries. Within four months (16 December 1784), the London publishing house of Joseph Johnson was announcing the publication of a complete English version, translated by William Godwin (i.e., Godwin, 1785), and, in between February and July 1785, four different "periodical abridgements of the Franklin report, each printed multiple times in the Atlantic coast publications" were published in the United States (Ogden, 2012, p. 167); and, in 1837, Godwin's complete translation was published, in Philadelphia, as part of a collected work. ==== Touch, imagination, and imitation ==== Clearly "recogniz[ing] that publicly endorsing the curative effects of a technique that had no demonstrable basis in the science of the late 18th century could lead to a proliferation of medical quackery" (McConkey & Perry, 2002, p. 328) and, based on their own "experiments" and "observations", the Commissioners concluded that "the true causes of the effects attributed to this new agent known by the name of animal magnetism, [and] to this fluid which is said to circulate in the body and to communicate itself


id: royal-commission-on-animal-magnetism-20260505-12
file: data/en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism-12.md
category: reference
title: Royal Commission on Animal Magnetism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism
date_saved: 2026-05-05T03:45:20.529918+00:00
instance: kb-cron
parent: royal-commission-on-animal-magnetism-20260505-0
summary:
On 4 September 1784, Bailly presented a third, brief (15 page) courtesy report to the Royal Academy of Sciences (Bailly, 1784b) on behalf of himself, Franklin, Le Roy, de Bory, and Lavoisier (i.e., those Commissioners who were also Academy members), which provided their Academy colleagues with a brief account of the commission's proceedings, the rationale behind its investigations, and the results. Noting that all of their investigations were jointly conducted with the four members of the Paris Faculty, and that all nine shared the same "interest in [discovering] the truth", they stressed that all the findings of their combined efforts were unanimous (p. 2). ==== The importance of "the Sciences" ==== Further (p. 4), given that the understanding of the Sciences – "which [collectively] are increased by [establishing] the truth" (qui s'accroissent par les vérités) – is increased by "the suppression of error": i.e., given that "error" is always "a bad leaven that ferments and, in the long run, corrupts the mass into which it has been introduced". By contrast, however, in those cases wherein the "error" has been generated by "The Empire of Science", and has spread to "the multitude" – not only to divide and agitate minds, but


id: royal-commission-on-animal-magnetism-20260505-13
file: data/en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism-13.md
category: reference
title: Royal Commission on Animal Magnetism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism
date_saved: 2026-05-05T03:45:20.529918+00:00
instance: kb-cron
parent: royal-commission-on-animal-magnetism-20260505-0
summary:
Part One (pp. 2–21), discussing the theories of the practices known as "Animal Magnetism". It commences with d'Eslon's definition of "animal magnetism"; namely that it is "the action which one man exercises on another, either through immediate contact or at a certain distance by the mere pointing of a finger or any kind of conduct", and that "this action", according to d'Eslon, "is the effect of a fluid that is distributed throughout the universe" Part Two (pp. 22–37), discussing the procedures and practices of "Animal Magnetism", as well as addressing the issues of their therapeutic efficacy (or not), and those of whether (or not) the procedures/practices should be admitted to conventional medical practice ("doivent-ils être admis en Médecine!": p. 22). The conclusions drawn (pp. 37–39) were, in brief, that they had found no evidence of d'Eslon's "magnetic fluid", that there were "no grounds for any belief in animal magnetism", that "the effects attributed to it are due to known causes", including not only the influence of "contact", "imagination", and/or "imitation", but also the influence of "the environment of the treatment room with its closed windows, fetid air, dim light, and the sight of other patients [and their responses to their


id: royal-commission-on-animal-magnetism-20260505-14
file: data/en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism-14.md
category: reference
title: Royal Commission on Animal Magnetism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism
date_saved: 2026-05-05T03:45:20.529918+00:00
instance: kb-cron
parent: royal-commission-on-animal-magnetism-20260505-0
summary:
=== Response of the Paris Faculty of Medicine === Immediately following the release of the reports of the two Commissions, the Paris Faculty of Medicine "pressure[d] its own members to renounce animal magnetism" (Crabtree, 1993, p. 32). The Faculty identified some thirty of its docteurs-régent, including François Louis Thomas d'Onglée and Charles-Louis Varnier, who "openly favored animal magnetism or were suspected of so doing". According to the contemporary account of Thomas d'Onglée (1785, passim), the thirty "magnetic physicians" were subjected to "abuse" and were presented with a declaration, of which it was demanded that they sign. Both Thomas d'Onglée and Varnier, among others, refused to sign the declaration (and were, thereby, immediately expelled). The declaration in question read: No Doctor may declare himself a partisan of animal magnetism, through writings or through practice, under penalty of being removed from the role of docteurs-régents. === D'Eslon's response === D'Eslon immediately published an attack on the commission's reports, in which he criticized their failure to investigate the longer-term effects of his treatments, and their refusal to accept his (alleged) "cures" as proof of the existence of "animal magnetism", as well as noting that, "the commissioners' recommendation that the practice of magnetism should


id: royal-commission-on-animal-magnetism-20260505-15
file: data/en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism-15.md
category: reference
title: Royal Commission on Animal Magnetism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism
date_saved: 2026-05-05T03:45:20.529918+00:00
instance: kb-cron
parent: royal-commission-on-animal-magnetism-20260505-0
summary:
The "classic" structure of the investigations undertaken by the "Franklin" Commission inspired – among many others over the ensuing years – the (1799) investigations of Chester physician John Haygarth (1740–1827) into the efficacy of Perkins' "tractors". In the process of discussing the experiments he had conducted (with medical colleagues as witnesses) with (dummy) "wooden tractors" on 7 January 1799, and with Perkins' "true metallick tractors" on 8 January 1799, Haygarth emphasized his considerable debt to the (earlier) "Franklin Commission" enterprise: It need not be remarked, how completely the trial illustrates the nature of this popular illusion, which has so wonderfully prevailed, and spread so rapidly; it resembles, in a striking manner, that of Animal Magnetism, which merited the attention of Dr. Franklin, when ambassador from America, and of other philosophers at Paris. If any person would repeat these experiments, they should be performed with due solemnity. During the process, the wonderful cures which this remedy is said to have performed ought to be particularly related. Without these indispensable aids, other trials will not prove as successful as those which are above reported. The whole effect undoubtedly depends upon the impression which can be made upon the patient's Imagination. This method


id: royal-commission-on-animal-magnetism-20260505-16
file: data/en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism-16.md
category: reference
title: Royal Commission on Animal Magnetism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Royal_Commission_on_Animal_Magnetism
date_saved: 2026-05-05T03:45:20.529918+00:00
instance: kb-cron
parent: royal-commission-on-animal-magnetism-20260505-0
summary:
The noted neurologist and psychoanalyst Sigmund Freud not only studied and wrote about "hypnosis" (e.g., Freud, 1891, and 1966), but he also actively used "hypnosis" in his clinical practice for some time. However the (à la Salpêtrière) "hypnosis" that Freud employed – quite unlike the conventional "hypnotism" of James Braid (that was induced by Braid's standard "upwards and inwards squint") – relied upon an induction process that often involved rubbing the top of a patient's head. This requirement, of course, demanded that Freud sat at the end of the therapeutic couch – in order to gain easy access to his subject's head – a practice that Freud continued to follow for his entire (post-"hypnosis") professional career. Another vestige of phreno-magnetism that demanded that Freud position himself at the patient's head was Freud's application of the "head pressure" technique that he had, in person, observed Hippolyte Bernheim use, on one of his visits to Bernheim's clinic at Nancy in 1899. Freud had discontinued this "head pressure" practice by, at least, 1904 – and, possibly, by 1900. === Mistaken identification of Esdaile's Jhar-Phoonk with d’Eslon's magnetization-by-contact === Due, to a large extent, to the (mistaken) enthusiastic promotion of Esdaile's (otherwise) valuable work


id: sampling-statistics-20260505-0
file: data/en.wikipedia.org/wiki/Sampling_(statistics)-0.md
category: reference
title: Sampling (statistics)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Sampling_(statistics)
date_saved: 2026-05-05T03:45:25.903358+00:00
instance: kb-cron
parent: sampling-statistics-20260505-0
summary:
In statistics, quality assurance, and survey methodology, sampling is the selection of a subset of individuals from within a statistical population to estimate characteristics of the whole population. The subset, called a statistical sample (or sample, for short), is meant to reflect the whole population, and statisticians attempt to collect samples that are representative of the population. Sampling has lower costs and faster data collection compared to a census recording data from the entire population (in many cases, collecting the whole population is impossible, like getting sizes of all stars in the universe). Thus, it can provide insights in cases where it is infeasible to measure an entire population. Each observation measures one or more properties (such as weight, location, colour or mass) of independent objects or individuals. In survey sampling, weights can be applied to the data to adjust for the sample design, particularly in stratified sampling. Results from probability theory and statistical theory are employed to guide the practice. In business and medical research, sampling is widely used for gathering information about a population. Acceptance sampling is used to determine if a production lot of material meets the governing specifications. == History == Random sampling by using lots


id: sampling-statistics-20260505-1
file: data/en.wikipedia.org/wiki/Sampling_(statistics)-1.md
category: reference
title: Sampling (statistics)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Sampling_(statistics)
date_saved: 2026-05-05T03:45:25.903358+00:00
instance: kb-cron
parent: sampling-statistics-20260505-0
summary:
In the most straightforward case, such as the sampling of a batch of material from production (acceptance sampling by lots), it would be most desirable to identify and measure every single item in the population and to include any one of them in our sample. However, in the more general case this is not usually possible or practical. There is no way to identify all rats in the set of all rats. Where voting is not compulsory, there is no way to identify which people will vote at a forthcoming election (in advance of the election). These imprecise populations are not amenable to sampling in any of the ways below and to which we could apply statistical theory. As a remedy, we seek a sampling frame which has the property that we can identify every single element and include any in our sample. The most straightforward type of frame is a list of elements of the population (preferably the entire population) with appropriate contact information. For example, in an opinion poll, possible sampling frames include an electoral register and a telephone directory. A probability sample is a sample in which every unit in the population has a chance (greater than


id: sampling-statistics-20260505-2
file: data/en.wikipedia.org/wiki/Sampling_(statistics)-2.md
category: reference
title: Sampling (statistics)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Sampling_(statistics)
date_saved: 2026-05-05T03:45:25.903358+00:00
instance: kb-cron
parent: sampling-statistics-20260505-0
summary:
In a simple random sample (SRS) of a given size, all subsets of a sampling frame have an equal probability of being selected. Each element of the frame thus has an equal probability of selection: the frame is not subdivided or partitioned. Furthermore, any given pair of elements has the same chance of selection as any other such pair (and similarly for triples, and so on). This minimizes bias and simplifies analysis of results. In particular, the variance between individual results within the sample is a good indicator of variance in the overall population, which makes it relatively easy to estimate the accuracy of results. Simple random sampling can be vulnerable to sampling error because the randomness of the selection may result in a sample that does not reflect the makeup of the population. For instance, a simple random sample of ten people from a given country will on average produce five men and five women, but any given trial is likely to overrepresent one sex and underrepresent the other. Systematic and stratified techniques attempt to overcome this problem by "using information about the population" to choose a more "representative" sample. Also, simple random sampling can be cumbersome and tedious


id: sampling-statistics-20260505-3
file: data/en.wikipedia.org/wiki/Sampling_(statistics)-3.md
category: reference
title: Sampling (statistics)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Sampling_(statistics)
date_saved: 2026-05-05T03:45:25.903358+00:00
instance: kb-cron
parent: sampling-statistics-20260505-0
summary:
When the population embraces a number of distinct categories, the frame can be organized by these categories into separate "strata." Each stratum is then sampled as an independent sub-population, out of which individual elements can be randomly selected. The ratio of the size of this random selection (or sample) to the size of the population is called a sampling fraction. There are several potential benefits to stratified sampling. First, dividing the population into distinct, independent strata can enable researchers to draw inferences about specific subgroups that may be lost in a more generalized random sample. Second, utilizing a stratified sampling method can lead to more efficient statistical estimates (provided that strata are selected based upon relevance to the criterion in question, instead of availability of the samples). Even if a stratified sampling approach does not lead to increased statistical efficiency, such a tactic will not result in less efficiency than would simple random sampling, provided that each stratum is proportional to the group's size in the population. Third, it is sometimes the case that data are more readily available for individual, pre-existing strata within a population than for the overall population; in such cases, using a stratified sampling approach may


id: sampling-statistics-20260505-4
file: data/en.wikipedia.org/wiki/Sampling_(statistics)-4.md
category: reference
title: Sampling (statistics)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Sampling_(statistics)
date_saved: 2026-05-05T03:45:25.903358+00:00
instance: kb-cron
parent: sampling-statistics-20260505-0
summary:
Example: Suppose we have six schools with populations of 150, 180, 200, 220, 260, and 490 students respectively (total 1500 students), and we want to use student population as the basis for a PPS sample of size three. To do this, we could allocate the first school numbers 1 to 150, the second school 151 to 330 (= 150 + 180), the third school 331 to 530, and so on to the last school (1011 to 1500). We then generate a random start between 1 and 500 (equal to 1500/3) and count through the school populations by multiples of 500. If our random start was 137, we would select the schools which have been allocated numbers 137, 637, and 1137, i.e. the first, fourth, and sixth schools. The PPS approach can improve accuracy for a given sample size by concentrating sample on large elements that have the greatest impact on population estimates. PPS sampling is commonly used for surveys of businesses, where element size varies greatly and auxiliary information is often available – for instance, a survey attempting to measure the number of guest-nights spent in hotels might use each hotel's number of rooms as an auxiliary variable. In some


id: sampling-statistics-20260505-5
file: data/en.wikipedia.org/wiki/Sampling_(statistics)-5.md
category: reference
title: Sampling (statistics)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Sampling_(statistics)
date_saved: 2026-05-05T03:45:25.903358+00:00
instance: kb-cron
parent: sampling-statistics-20260505-0
summary:
Accidental sampling (sometimes known as grab, convenience, or opportunity sampling) is a type of nonprobability sampling which involves the sample being drawn from that part of the population which is close to hand. That is, a population is selected because it is readily available and convenient. It may be through meeting the person or including a person in the sample when one meets them or chosen by finding them through technological means such as the internet or through phone. The researcher using such a sample cannot scientifically make generalizations about the total population from this sample because it would not be representative enough. For example, if the interviewer were to conduct such a survey at a shopping center early in the morning on a given day, the people that they could interview would be limited to those given there at that given time, which would not represent the views of other members of society in such an area, if the survey were to be conducted at different times of day and several times per week. This type of sampling is most useful for pilot testing. Several important considerations for researchers using convenience samples include: Are there controls within the research


id: sampling-statistics-20260505-6
file: data/en.wikipedia.org/wiki/Sampling_(statistics)-6.md
category: reference
title: Sampling (statistics)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Sampling_(statistics)
date_saved: 2026-05-05T03:45:25.903358+00:00
instance: kb-cron
parent: sampling-statistics-20260505-0
summary:
Sampling schemes may be without replacement ('WOR' – no element can be selected more than once in the same sample) or with replacement ('WR' – an element may appear multiple times in the one sample). For example, if we catch fish, measure them, and immediately return them to the water before continuing with the sample, this is a WR design, because we might end up catching and measuring the same fish more than once. However, if we do not return the fish to the water or tag and release each fish after catching it, this becomes a WOR design. == Sample size determination == Formulas, tables, and power function charts are well known approaches to determine sample size. Steps for using sample size tables: Postulate the effect size of interest, α, and β. Check sample size table Select the table corresponding to the selected α Locate the row corresponding to the desired power Locate the column corresponding to the estimated effect size. The intersection of the column and row is the minimum sample size required. == Sampling and data collection == Good data collection involves: Following the defined sampling process Keeping the data in time order Noting comments and other


id: sampling-statistics-20260505-7
file: data/en.wikipedia.org/wiki/Sampling_(statistics)-7.md
category: reference
title: Sampling (statistics)
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Sampling_(statistics)
date_saved: 2026-05-05T03:45:25.903358+00:00
instance: kb-cron
parent: sampling-statistics-20260505-0
summary:
Robert Groves, et alia. Survey methodology (2010 2nd ed. [2004]) ISBN 0-471-48348-6. The other books focus on the statistical theory of survey sampling and require some knowledge of basic statistics, as discussed in the following textbooks: David S. Moore and George P. McCabe (February 2005). "Introduction to the practice of statistics" (5th edition). W.H. Freeman & Company. ISBN 0-7167-6282-X. Freedman, David; Pisani, Robert; Purves, Roger (2007). Statistics (4th ed.). New York: Norton. ISBN 978-0-393-92972-0. The elementary book by Scheaffer et alia uses quadratic equations from high-school algebra: Scheaffer, Richard L., William Mendenhal and R. Lyman Ott. Elementary survey sampling, Fifth Edition. Belmont: Duxbury Press, 1996. More mathematical statistics is required for Lohr, for Särndal et alia, and for Cochran: Cochran, William G. (1977). Sampling techniques (Third ed.). Wiley. ISBN 978-0-471-16240-7. Lohr, Sharon L. (1999). Sampling: Design and analysis. Duxbury. ISBN 978-0-534-35361-2. Särndal, Carl-Erik; Swensson, Bengt; Wretman, Jan (1992). Model assisted survey sampling. Springer-Verlag. ISBN 978-0-387-40620-6. The historically important books by Deming and Kish remain valuable for insights for social scientists (particularly about the U.S. census and the Institute for Social Research at the University of Michigan): Deming, W. Edwards (1966). Some Theory of Sampling. Dover Publications. ISBN 978-0-486-64684-8. OCLC 166526.


id: science-of-team-science-20260505-0
file: data/en.wikipedia.org/wiki/Science_of_team_science-0.md
category: reference
title: Science of team science
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Science_of_team_science
date_saved: 2026-05-05T03:45:27.166660+00:00
instance: kb-cron
parent: science-of-team-science-20260505-0
summary:
Science of Team Science (SciTS) is a field of methodology that focuses on understanding and improving cross-disciplinary collaboration in research. The field encompasses conceptual and methodological strategies to understand how teams of scientific researchers can be organized to work more effectively. SciTS initiatives involve understanding and managing factors that affect collaborative science and assessing its outcomes. == History == Since the 1990s, interest and large-scale funding for team-based research initiatives has increased, driven by efforts to tackle complex problems through cross-disciplinary collaboration. Some argue that this trend reflects the growing recognition that addressing multifaceted challenges, such as climate change and public health issues, benefit from partnerships among scientists and practitioners from diverse fields. One SciTS literature review highlighted team science as essential to interprofessional collaborative research. The report called for its integration into health professions education and clinical practice at the University of Minnesota's National Center for Interprofessional Practice and Education. The interdisciplinary nature of SciTS initially emerged from concerns raised by funding agencies, which sought to assess the performance of team science, understand its added value, evaluate the return on investment in large research initiatives, and inform science policy. The term "science of team science" was first introduced in


id: science-on-the-verge-20260505-0
file: data/en.wikipedia.org/wiki/Science_on_the_Verge-0.md
category: reference
title: Science on the Verge
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Science_on_the_Verge
date_saved: 2026-05-05T03:45:28.491279+00:00
instance: kb-cron
parent: science-on-the-verge-20260505-0
summary:
Science on the verge is a book written in 2016 by group of eight scholars working in the tradition of Post-normal science. The book analyzes the main features and possible causes of the present science's crisis. == Content == Science on the verge, written by Alice Benessia, Silvio Funtowicz, Mario Giampietro, Ângela Guimarães Pereira, Jerome Ravetz, Andrea Saltelli, Roger Strand, and Jeroen P. van der Sluijs, with a preface by Dan Sarewitz, follows different threads of the present science's crisis (lost reproducibility, collapsing peer review, perverse metrics, evidence based policy's dysfunctions, techno-science and its hubris, science as metaphysics ...) and presents a first systematic analysis of the main causes of the present predicaments. Chapter 1. The chapter entitled 'Who will solve the crisis in science?' tackles the following questions: Is there a crisis? What is being done 'from within'? Is this sufficient? What are the diagnoses for the crisis' root causes, and what are the solutions 'from without'? Chapter 2. This is chapter entitled 'The fallacy of evidence based policy' tackles: Quantification as hypocognition; Socially constructed ignorance & uncomfortable knowledge; Ancien régime syndrome; Quantitative story telling. Chapter 3. This is chapter entitled 'Never late, never lost, never unprepared' treats: Trajectories


id: scientific-collection-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_collection-0.md
category: reference
title: Scientific collection
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_collection
date_saved: 2026-05-05T03:45:29.768232+00:00
instance: kb-cron
parent: scientific-collection-20260505-0
summary:
A scientific collection is a collection of items that are preserved, catalogued, and managed for the purpose of scientific study. Scientific collections dealing specifically with organisms plants, fungi, animals, insects and their remains, may also be called natural history collections or biological collections. The latter may contain either living stocks or preserved repositories of biodiversity specimens and materials. Scientific collections hold a tangible portion of the cumulative evidence base in such fields as biology (especially taxonomy and evolutionary biology), geology, and archaeology. They may be stored and managed by governments, educational institutions (e.g. colleges and universities), private organizations (including museums), or individuals. Prominent uses of scientific collections include the systematic description and identification of biological species, the study and prediction of long-term historical trends (including impacts of climate change), the dating and analysis of historical objects (e.g. via wood samples and ice cores with annual rings), and the maintenance of teaching resources. == Indexing == The indexing of the collections was historically made by directories, catalogs, index cards, today supplemented by or replaced by databases with information such as e.g. scientific description, including picture, name, location, find circumstances, fund age, scientific analysis, phylogenetic relationships, DNA and isotope analysis results, analysis


id: scientific-collection-20260505-1
file: data/en.wikipedia.org/wiki/Scientific_collection-1.md
category: reference
title: Scientific collection
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_collection
date_saved: 2026-05-05T03:45:29.768232+00:00
instance: kb-cron
parent: scientific-collection-20260505-0
summary:
in France: Muséum National d'Histoire Naturelle, Paris contains 9,500,000 specimens; Université Montpellier contains 4,000,000 specimens; Université Claude Bernard Lyon 1 contains 4,000,000 specimens in Russia: Komarov Botanical Institute in St. Petersburg contains 7,160,000 specimens, in Great Britain: Royal Botanic Gardens Kew contains 7,000,000 specimens; British Museum of Natural History contains 80,000,000 specimens; Royal Botanic Garden Edinburgh contains 2,000,000 specimens; University of Cambridge contains 1,000,000 specimens; University of Manchester contains 1,000,000 specimens; in Switzerland: Conservatoire et Jardin botaniques de la Ville de Genève contains 6,000,000 specimens; Eidgenössische Technische Hochschule Zürich contains 1,500,000 specimens, in Austria: Naturhistorisches Museum Wien contains 5,000,000 specimens; Universität Wien contains 1,400,000 specimens, in Sweden: Swedish Museum of Natural History (Naturhistoriska riksmuseet) contains 4,400,000 specimens; Uppsala University contains 3,000,000 specimens, Botanical Museum, Lund contains 2,500,000 specimens, University of Gothenburg contains 1,600,000 specimens, in Netherlands: National Herbarium of the Netherlands (Nationaal Herbarium Nederland) contains 4,000,000 specimens in Italy: Museo di Storia Naturale dell'Università, Florence contains 3,650,000 specimens; Università degli Studi di Roma La Sapienza, Rome contains 1,120,000 specimens; Università degli Studi di Torino contains 1,000,000 specimens, in Belgium: National Botanic Garden of Belgium contains 3,500,000 specimens, in Germany: Botanischer Garten und Botanisches Museum Berlin-Dahlem, Zentraleinrichtung der Freien Universität Berlin


id: scientific-control-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_control-0.md
category: reference
title: Scientific control
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_control
date_saved: 2026-05-05T03:45:31.111708+00:00
instance: kb-cron
parent: scientific-control-20260505-0
summary:
A scientific control is an element of an experiment or observation designed to minimize the influence of variables other than the independent variable under investigation, thereby reducing the risk of confounding. The use of controls increases the reliability and validity of results by providing a baseline for comparison between experimental measurements and control measurements. In many designs, the control group does not receive the experimental treatment, allowing researchers to isolate the effect of the independent variable. Scientific controls are a fundamental part of the scientific method, particularly in fields such as biology, chemistry, medicine, and psychology, where complex systems are subject to multiple interacting variables. == Controlled experiments == Controls eliminate alternate explanations of experimental results, especially experimental errors and experimenter bias. Many controls are specific to the type of experiment being performed, as in the molecular markers used in SDS-PAGE experiments, and may simply have the purpose of ensuring that the equipment is working properly. The selection and use of proper controls to ensure that experimental results are valid (for example, absence of confounding variables) can be very difficult. Control measurements may also be used for other purposes: for example, a measurement of a microphone's background noise in the


id: scientific-control-20260505-1
file: data/en.wikipedia.org/wiki/Scientific_control-1.md
category: reference
title: Scientific control
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_control
date_saved: 2026-05-05T03:45:31.111708+00:00
instance: kb-cron
parent: scientific-control-20260505-0
summary:
Negative controls are variables that meant to help when the study design is suspected to be invalid because of unmeasured confounders that are correlated with both the treatment and the outcome. Where there are only two possible outcomes, e.g. positive or negative, if the treatment group and the negative control (non-treatment group) both produce a negative result, it can be inferred that the treatment had no effect. If the treatment group and the negative control both produce a positive result, it can be inferred that a confounding variable is involved in the phenomenon under study, and the positive results are not solely due to the treatment. In other examples, outcomes might be measured as lengths, times, percentages, and so forth. In the drug testing example, we could measure the percentage of patients cured. In this case, the treatment is inferred to have no effect when the treatment group and the negative control produce the same results. Some improvement is expected in the placebo group due to the placebo effect, and this result sets the baseline upon which the treatment must improve upon. Even if the treatment group shows improvement, it needs to be compared to the placebo group. If the


id: scientific-control-20260505-2
file: data/en.wikipedia.org/wiki/Scientific_control-2.md
category: reference
title: Scientific control
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_control
date_saved: 2026-05-05T03:45:31.111708+00:00
instance: kb-cron
parent: scientific-control-20260505-0
summary:
Y ~ ⊥ A | U , X {\displaystyle {\tilde {Y}}\perp A|\;U,X} : There is no causal effect of A {\displaystyle A} on Y ~ {\displaystyle {\tilde {Y}}} given X {\displaystyle X} and U {\displaystyle U} . The NCO is independent of the treatment given X {\displaystyle X} and U {\displaystyle U} . U-Comparability: Y ~ ⧸ ⊥ U | X {\displaystyle {\tilde {Y}}\not {\perp }U|\;X} The unmeasured confounders U {\displaystyle U} of the association between A {\displaystyle A} and Y {\displaystyle Y} are the same for the association between A {\displaystyle A} and Y ~ {\displaystyle {\tilde {Y}}} . Given assumption 1 - 4, a non-null association between A {\displaystyle A} and Y ~ {\displaystyle {\tilde {Y}}} , can be explained by U {\displaystyle U} , and not by another mechanism. A possible violation of Latent Exchangeability will be when only the people that are influenced by a medicine will take it, even if both X {\displaystyle X} and U {\displaystyle U} are the same. For example, we would expect that given age and medical history ( X {\displaystyle X} ), general health awareness ( U {\displaystyle U} ), the intake of A {\displaystyle A} influenza vaccine will be


id: scientific-control-20260505-3
file: data/en.wikipedia.org/wiki/Scientific_control-3.md
category: reference
title: Scientific control
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_control
date_saved: 2026-05-05T03:45:31.111708+00:00
instance: kb-cron
parent: scientific-control-20260505-0
summary:
Blinding is the practice of withholding information that may bias an experiment. For example, participants may not know who received an active treatment and who received a placebo. If this information were to become available to trial participants, patients could receive a larger placebo effect, researchers could influence the experiment to meet their expectations (the observer effect), and evaluators could be subject to confirmation bias. A blind can be imposed on any participant of an experiment, including subjects, researchers, technicians, data analysts, and evaluators. In some cases, sham surgery may be necessary to achieve blinding. During the course of an experiment, a participant becomes unblinded if they deduce or otherwise obtain information that has been masked to them. Unblinding that occurs before the conclusion of a study is a source of experimental error, as the bias that was eliminated by blinding is re-introduced. Unblinding is common in blind experiments and must be measured and reported. Meta-research has revealed high levels of unblinding in pharmacological trials. In particular, antidepressant trials are poorly blinded. Reporting guidelines recommend that all studies assess and report unblinding. In practice, very few studies assess unblinding. Blinding is an important tool of the scientific method, and is


id: scientific-dissent-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_dissent-0.md
category: reference
title: Scientific dissent
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_dissent
date_saved: 2026-05-05T03:45:32.446115+00:00
instance: kb-cron
parent: scientific-dissent-20260505-0
summary:
Scientific dissent is dissent from scientific consensus. Disagreements can be useful for finding problems in underlying assumptions, methodologies, and reasoning, as well as for generating and testing new ways of tackling the unknown. In modern times, with the increased role of science on the society and the politicization of science, a new aspect gained prominence: effects of scientific dissent on public policies. Scientific dissent is distinct from denialism, which is a deliberate rejection of scientific consensus usually for commercial or ideological reasons. == Dissent as part of scientific inquiry == Miriam Solomon in her book Social Empiricism argues that scientific dissent is the normal state of scientific inquiry, rather than a conflict that needs resolution. She argues that disagreements between individual scientists about the proper direction of research are not cause for concern, because scientific rationality must be assessed at the level of the scientific community. As long as all theories being pursued yield some unique empirical successes, Solomon argues that their pursuit is worthwhile and consistent with the common view that science aims at truth. In Solomon's view, competing scientific theories can even be inconsistent with one another while each containing some degree of truth. Empirical evidence may not


id: scientific-enterprise-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_enterprise-0.md
category: reference
title: Scientific enterprise
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_enterprise
date_saved: 2026-05-05T03:45:33.771589+00:00
instance: kb-cron
parent: scientific-enterprise-20260505-0
summary:
A scientific enterprise is a science-based project developed by, or in cooperation with, a private entrepreneur. For example, in the Age of Exploration, leaders like Henry the Navigator founded schools of navigation, from which stemmed voyages of exploration. == Examples of enterprising scientific organizations == Each organization listed below has the ability to conduct scientific research on an extended basis, involving multiple researchers over an extended time. Generally, the research is funded not only for the science itself, but for some application which shows promise for the enterprise. But the researchers, if left to their own choices, will tend to follow their research interest, which is essential for the long-term health of their chosen field. Note that a successful scientific enterprise is not equivalent to a successful high-tech enterprise or to a successful business enterprise, but that they form an ecology, a food chain. The Max Planck Institute, which supports fundamental research in the natural, life and social sciences, the arts and humanities The RAND Corporation, founded as a research corporation. Did groundbreaking work in the field of artificial intelligence The Jet Propulsion Laboratory, founded by Theodore von Kármán Bell Laboratories, renowned for the quality of its scientific work and


id: scientific-evidence-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_evidence-0.md
category: reference
title: Scientific evidence
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_evidence
date_saved: 2026-05-05T03:45:34.945725+00:00
instance: kb-cron
parent: scientific-evidence-20260505-0
summary:
Scientific evidence is evidence that serves to either support or counter a scientific theory or hypothesis, although scientists also use evidence in other ways, such as when applying theories to practical problems. Such evidence is expected to be empirical evidence and interpretable in accordance with the scientific method. Standards for scientific evidence vary according to the field of inquiry, but the strength of scientific evidence is generally based on the results of statistical analysis and the strength of scientific controls. == Principles of inference == A person's assumptions or beliefs about the relationship between observations and a hypothesis will affect whether that person takes the observations as evidence. These assumptions or beliefs will also affect how a person utilizes the observations as evidence. For example, the Earth's apparent lack of motion may be taken as evidence for a geocentric cosmology. However, after sufficient evidence is presented for heliocentric cosmology and the apparent lack of motion is explained, the initial observation is strongly discounted as evidence. When rational observers have different background beliefs, they may draw different conclusions from the same scientific evidence. For example, Priestley, working with phlogiston theory, explained his observations about the decomposition of mercuric oxide using phlogiston.


id: scientific-evidence-20260505-1
file: data/en.wikipedia.org/wiki/Scientific_evidence-1.md
category: reference
title: Scientific evidence
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_evidence
date_saved: 2026-05-05T03:45:34.945725+00:00
instance: kb-cron
parent: scientific-evidence-20260505-0
summary:
== Philosophical versus scientific views == In the 20th century, many philosophers investigated the logical relationship between evidence statements and hypotheses, whereas scientists tended to focus on how the data used for statistical inference are generated. But according to philosopher Deborah Mayo, by the end of the 20th century philosophers had come to understand that "there are key features of scientific practice that are overlooked or misdescribed by all such logical accounts of evidence, whether hypothetico-deductive, Bayesian, or instantiationist". There were a variety of 20th-century philosophical approaches to decide whether an observation may be considered evidence; many of these focused on the relationship between the evidence and the hypothesis. In the 1950s, Rudolf Carnap recommended distinguishing such approaches into three categories: classificatory (whether the evidence confirms the hypothesis), comparative (whether the evidence supports a first hypothesis more than an alternative hypothesis) or quantitative (the degree to which the evidence supports a hypothesis). A 1983 anthology edited by Peter Achinstein provided a concise presentation by prominent philosophers on scientific evidence, including Carl Hempel (on the logic of confirmation), R. B. Braithwaite (on the structure of a scientific system), Norwood Russell Hanson (on the logic of discovery), Nelson Goodman (of grue fame,


id: scientific-formalism-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_formalism-0.md
category: reference
title: Scientific formalism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_formalism
date_saved: 2026-05-05T03:45:36.172732+00:00
instance: kb-cron
parent: scientific-formalism-20260505-0
summary:
Scientific formalism is a family of approaches to the presentation of science. It is viewed as an important part of the scientific method, especially in the physical sciences. == Levels of formalism == There are multiple levels of scientific formalism possible. At the lowest level, scientific formalism deals with the symbolic manner in which the information is presented. To achieve formalism in a scientific theory at this level, one starts with a well defined set of axioms, and from this follows a formal system. However, at a higher level, scientific formalism also involves consideration of the axioms themselves. These can be viewed as questions of ontology. For example, one can, at the lower level of formalism, define a property called 'existence'. However, at the higher level, the question of whether an electron exists in the same sense that a bacterium exists still needs to be resolved. Some actual formal theories on facts have been proposed. == In modern physics == The scientific climate of the twentieth century revived these questions. From about the time of Isaac Newton to that of James Clerk Maxwell they had been dormant, in the sense that the physical sciences could rely on the status of


id: scientific-imperialism-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_imperialism-0.md
category: reference
title: Scientific imperialism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_imperialism
date_saved: 2026-05-05T03:45:37.416247+00:00
instance: kb-cron
parent: scientific-imperialism-20260505-0
summary:
Scientific imperialism is a term that appears to have been coined by Ellis T. Powell when addressing the Commonwealth Club of Canada on 8 September 1920. He defined imperialism as "the sense of arbitrary and capricious domination over the bodies and souls of men," he used the term "scientific imperialism" to mean "the subjection of all the developed and undeveloped powers of the earth to the mind of man." In modern usage, however, scientific imperialism refers to situations in which critics perceive science to act imperiously. Philosopher of science John Dupré described it (in his 2001 book Human Nature and the Limits of Science, p. 74) as "the tendency to push a good scientific idea far beyond the domain in which it was originally introduced, and often far beyond the domain in which it can provide much illumination." He wrote that "devotees of these approaches are inclined to claim that they are in possession not just of one useful perspective on human behavior, but of the key that will open doors to the understanding of ever wider areas of human behavior." Scientific imperialism has also been charged against "those who believe that the study of politics can and should be


id: scientific-integrity-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_integrity-0.md
category: reference
title: Scientific integrity
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_integrity
date_saved: 2026-05-05T03:45:42.549163+00:00
instance: kb-cron
parent: scientific-integrity-20260505-0
summary:
Research integrity or scientific integrity is an aspect of research ethics that deals with best practice or rules of professional practice of scientists. First introduced in the 19th century by Charles Babbage, the concept of research integrity came to the fore in the late 1970s. A series of publicized scandals in the United States led to heightened debate on the ethical norms of sciences and the limitations of the self-regulation processes implemented by scientific communities and institutions. Formalized definitions of scientific misconduct, and codes of conduct, became the main policy response after 1990. In the 21st century, codes of conduct or ethics codes for research integrity are widespread. Along with codes of conduct at institutional and national levels, major international texts include the European Charter for Researchers (2005), the Singapore Statement on Research Integrity (2010), the European Code of Conduct for Research Integrity (2011 & 2017), and the Hong Kong Principles for assessing researchers (2020). Scientific literature on research integrity falls mostly into two categories: first, mapping of the definitions and categories, especially in regard to scientific misconduct, and second, empirical surveys of the attitudes and practices of scientists. Following the development of codes of conduct, taxonomies of non-ethical uses


id: scientific-integrity-20260505-1
file: data/en.wikipedia.org/wiki/Scientific_integrity-1.md
category: reference
title: Scientific integrity
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_integrity
date_saved: 2026-05-05T03:45:42.549163+00:00
instance: kb-cron
parent: scientific-integrity-20260505-0
summary:
=== Emergence of the issue === Before the 1970s, ethical issues were largely focused on the conduct of medical experiments, especially in regard to tests on humans. In 1803, the "code" of Thomas Percival created a moral foundation for experimental treatments that "was built upon fairly regularly" throughout the next two centuries, notably by Walter Reed in 1898 and by the Berlin code in 1900. After the Second World War, the Nazi human experimentations motivated the development of international, widely acknowledged codes of research ethics, such as the Nuremberg code (1947) and the World Medical Association Declaration of Helsinki. According to Kenneth Pimple, Charles Babbage was the first author to set aside the specific issue of scientific integrity. In the Reflections on the Decline of Science in England, and on Some of its Causes, first published in 1830, Babbage identified four classes of scientific frauds, from outright forgery to varied degrees of arrangements and cooking of the data or the methods. Research integrity became a major debated topic in biological sciences after 1970, due to a combination of factors: the development of advanced data analysis methods, the growing commercial relevancy of fundamental research, and the increased focus of federal funding


id: scientific-integrity-20260505-2
file: data/en.wikipedia.org/wiki/Scientific_integrity-2.md
category: reference
title: Scientific integrity
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_integrity
date_saved: 2026-05-05T03:45:42.549163+00:00
instance: kb-cron
parent: scientific-integrity-20260505-0
summary:
== Taxonomy and classification == In codes of conduct, the definition of research integrity is usually negative: the collection of norms aims to single out different forms of unethical research and scientific misconduct with varying degrees of gravity. The multiplication of codes of conduct has also corresponded with an expansion of scope. While the initial debate was focused on "three deadly sins of scientific and scholarly research: fabrication, falsification and plagiarism", attention has later shifted "to the lesser breaches of research integrity". In 1830, Charles Babbage introduced the first taxonomy of scientific frauds that already encover some forms of questionable research practices : hoaxing (a voluntary fraud "far from justifiable"), forging ("whereas the forger is one who, wishing to acquire a reputation for science, records observations which he has never made"), trimming (which "consists in clipping off little bits here and there from those observations which differ most in excess from the mean" and cooking. Cooking is the main focus of Babbage as an "art of various forms, the object of which is to give to ordinary observations the appearance and character of those of the highest degree of accuracy". It falls done under several sub-cases such as data selection


id: scientific-integrity-20260505-3
file: data/en.wikipedia.org/wiki/Scientific_integrity-3.md
category: reference
title: Scientific integrity
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_integrity
date_saved: 2026-05-05T03:45:42.549163+00:00
instance: kb-cron
parent: scientific-integrity-20260505-0
summary:
=== Implementation and assessment of codes of conduct === Several case studies and retrospective analyses have been devoted to the reception of codes of conduct in scientific communities. They frequently highlight a discrepancy between the theoretical norms and the "lived morality of researchers". In 2004, Caroline Whitbeck underlined that the enforcement of a few formal rules has overall failed to answer to a structural "erosion or neglect" of scientific trust. In 2009, Schuurbiers, Osseweijer and Kinderler led a series of interviews in the aftermath of the Dutch code of conduct on research integrity, introduced in 2005. Overall, most respondents were unaware of the code and complementary ethical recommendations. While the principles "were seen to reflect the norms and values within science rather well", they seemed to be isolated from the actual work practices, which "may lead to morally complex situations". Respondents were also critical of the underlying individualist philosophy of the code, which shifted the entire blame to individual researchers without taking into account institutional or community-wide issues. In 2015, a survey of "64 faculty members at a large southwestern university" in the United States "yielded similar results": many of the respondents were not aware of the existing ethical guidelines,


id: scientific-integrity-20260505-4
file: data/en.wikipedia.org/wiki/Scientific_integrity-4.md
category: reference
title: Scientific integrity
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_integrity
date_saved: 2026-05-05T03:45:42.549163+00:00
instance: kb-cron
parent: scientific-integrity-20260505-0
summary:
In 2018, Heidi Laine attempted to establish a nearly-exhaustive list of "ethical principles associated with open science": This categorization has to contend with the diversity of approaches and values associated with the open science movement and their ongoing evolutions, as the "term will likely remain as fluid as any other attempt to coin a complex system of practices, values and ideologies in one term". Laine identified a significant variation in the way open science principles have been embedded in four major codes of conduct and statements on research integrity: the Singapore Statement on Research Integrity (2010), the Montreal Statement on Research Integrity in Cross-Boundary Research Collaborations (2013), the Responsible Conduct of Research and Procedures for Handling Allegations of Misconduct in Finland (2012) and the European Code of Conduct for Research Integrity (2017). Access to research publications is recommended in all four codes. Integrations of data sharing and reproducibility practices are less obvious, and vary from a tacit approval to detailed support, in the case of the later European Code of Conduct: "The European code pays data management almost an equal amount of attention as publishing and is also in this sense the most advanced of the four CoCs." Yet, important


id: scientific-integrity-20260505-5
file: data/en.wikipedia.org/wiki/Scientific_integrity-5.md
category: reference
title: Scientific integrity
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_integrity
date_saved: 2026-05-05T03:45:42.549163+00:00
instance: kb-cron
parent: scientific-integrity-20260505-0
summary:
In a statement made by the US Department of Health and Human Services (HHS), they adopted the definition of Scientific Integrity as stated below. This policy is currently being reviewed and will be officially published in early 2024." Scientific integrity is the adherence to professional practices, ethical behavior, and the principles of honesty and objectivity when conducting, managing, using the results of, and communicating about science and scientific activities. Inclusivity, transparency, and protection from inappropriate influence are hallmarks of scientific integrity."-HHS To promote a culture of scientific integrity at HHS, they have outlined their policy in seven specific areas: Protecting Scientific Processes Ensuring the Free Flow of Scientific Information Supporting Policymaking Processes Ensuring Accountability Protecting Scientists Professional Development for Government Scientists Federal Advisory Committees As a result of these areas, open science practices can be promoted to protect against bias, plagiarism, and data fabrication, falsification as well as inappropriate influencing, political interference, and censorship. ===== National Institute of Health ===== The National Institute of Health (NIH) is a branch of the HHS. They act as the nation's medical research agency which focuses on making important discoveries that improve health and save lives. The mission of NIH is to provide a


id: scientific-integrity-20260505-6
file: data/en.wikipedia.org/wiki/Scientific_integrity-6.md
category: reference
title: Scientific integrity
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_integrity
date_saved: 2026-05-05T03:45:42.549163+00:00
instance: kb-cron
parent: scientific-integrity-20260505-0
summary:
=== Journal articles === Woolf, Patricia K. (1988). "Deception in Scientific Research". Jurimetrics. 29 (1): 67–95. ISSN 0897-1277. JSTOR 29762108. PMID 11654908. Partha, Dasgupta; David, Paul A. (1994-09-01). "Toward a new economics of science". Research Policy. Special Issue in Honor of Nathan Rosenberg. 23 (5): 487–521. doi:10.1016/0048-7333(94)01002-1. ISSN 0048-7333. Pimple, Kenneth D. (2002-06-01). "Six domains of research ethics". Science and Engineering Ethics. 8 (2): 191–205. doi:10.1007/s11948-002-0018-1. ISSN 1471-5546. PMID 12092490. S2CID 25084326. Whitbeck, Caroline (2004). "Trust and the Future of Research". Physics Today. 57 (11): 48–53. Bibcode:2004PhT....57k..48W. doi:10.1063/1.1839377. ISSN 0031-9228. Retrieved 2022-02-12. Ioannidis, John P. A. (2005). "Why Most Published Research Findings Are False". PLOS Medicine. 2 (8): –124. doi:10.1371/journal.pmed.0020124. ISSN 1549-1676. PMC 1182327. PMID 16060722. Rappert, Brian (2007). "Codes of conduct and biological weapons: an in-process assessment". Biosecurity and Bioterrorism: Biodefense Strategy, Practice, and Science. 5 (2): 145–154. doi:10.1089/bsp.2007.0003. hdl:10036/32132. ISSN 1538-7135. PMID 17608600. David, Paul A. (2008-10-24). "The Historical Origins of 'Open Science': An Essay on Patronage, Reputation and Common Agency Contracting in the Scientific Revolution". Capitalism and Society. 3 (2). doi:10.2202/1932-0213.1040. ISSN 1932-0213. S2CID 41478207. Retrieved 2021-11-11. Schuurbiers, Daan; Osseweijer, Patricia; Kinderlerer, Julian (2009). "Implementing the Netherlands code of conduct for scientific practice-a case study". Science and


id: scientific-law-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_law-0.md
category: reference
title: Scientific law
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_law
date_saved: 2026-05-05T03:45:43.771670+00:00
instance: kb-cron
parent: scientific-law-20260505-0
summary:
Scientific laws or laws of science are statements, based on repeated experiments or observations, that describe or predict a range of natural phenomena. The term law has diverse usage in many cases (approximate, accurate, broad, or narrow) across all fields of natural science (physics, chemistry, astronomy, geoscience, biology). Laws are developed from data and can be further developed through mathematics; in all cases they are directly or indirectly based on empirical evidence. It is generally understood that they implicitly reflect, though they do not explicitly assert, causal relationships fundamental to reality, and are discovered rather than invented. Scientific laws summarize the results of experiments or observations, usually within a certain range of application. In general, the accuracy of a law does not change when a new theory of the relevant phenomenon is worked out, but rather the scope of the law's application, since the mathematics or statement representing the law does not change. As with other kinds of scientific knowledge, scientific laws do not express absolute certainty, as mathematical laws do. A scientific law may be contradicted, restricted, or extended by future observations. A law can often be formulated as one or several statements or equations, so that it can


id: scientific-law-20260505-1
file: data/en.wikipedia.org/wiki/Scientific_law-1.md
category: reference
title: Scientific law
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_law
date_saved: 2026-05-05T03:45:43.771670+00:00
instance: kb-cron
parent: scientific-law-20260505-0
summary:
== Properties == Scientific laws are typically conclusions based on repeated scientific experiments and observations over many years and which have become accepted universally within the scientific community. A scientific law is "inferred from particular facts, applicable to a defined group or class of phenomena, and expressible by the statement that a particular phenomenon always occurs if certain conditions be present". The production of a summary description of our environment in the form of such laws is a fundamental aim of science. Several general properties of scientific laws, particularly when referring to laws in physics, have been identified. Scientific laws are: True, at least within their regime of validity. By definition, there have never been repeatable contradicting observations. Universal. They appear to apply everywhere in the universe. Simple. They are typically expressed in terms of a single mathematical equation. Absolute. Nothing in the universe appears to affect them. Stable. Unchanged since first discovered (although they may have been shown to be approximations of more accurate laws), All-encompassing. Everything in the universe apparently must comply with them (according to observations). Generally conservative of quantity. Often expressions of existing homogeneities (symmetries) of space and time. Typically theoretically reversible in time (if non-quantum),


id: scientific-law-20260505-2
file: data/en.wikipedia.org/wiki/Scientific_law-2.md
category: reference
title: Scientific law
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_law
date_saved: 2026-05-05T03:45:43.771670+00:00
instance: kb-cron
parent: scientific-law-20260505-0
summary:
where ρ is some quantity per unit volume, J is the flux of that quantity (change in quantity per unit time per unit area). Intuitively, the divergence (denoted ∇⋅) of a vector field is a measure of flux diverging radially outwards from a point, so the negative is the amount piling up at a point; hence the rate of change of density in a region of space must be the amount of flux leaving or collecting in some region (see the main article for details). In the table below, the fluxes flows for various physical quantities in transport, and their associated continuity equations, are collected for comparison. More general equations are the convection–diffusion equation and Boltzmann transport equation, which have their roots in the continuity equation. === Laws of classical mechanics === ==== Principle of least action ==== Classical mechanics, including Newton's laws, Lagrange's equations, Hamilton's equations, etc., can be derived from the following principle: δ S = δ ∫ t 1 t 2 L ( q , q ˙ , t ) d t = 0 {\displaystyle \delta {\mathcal {S}}=\delta \int _{t_{1}}^{t_{2}}L(\mathbf {q} ,\mathbf {\dot {q}} ,t)\,dt=0} where S {\displaystyle {\mathcal {S}}} is the action; the integral of the


id: scientific-law-20260505-3
file: data/en.wikipedia.org/wiki/Scientific_law-3.md
category: reference
title: Scientific law
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_law
date_saved: 2026-05-05T03:45:43.771670+00:00
instance: kb-cron
parent: scientific-law-20260505-0
summary:
in which the (more famous) mass–energy equivalence E = mc2 is a special case. General relativity: General relativity is governed by the Einstein field equations, which describe the curvature of space-time due to mass-energy equivalent to the gravitational field. Solving the equation for the geometry of space warped due to the mass distribution gives the metric tensor. Using the geodesic equation, the motion of masses falling along the geodesics can be calculated. Gravitoelectromagnetism: In a relatively flat spacetime due to weak gravitational fields, gravitational analogues of Maxwell's equations can be found; the GEM equations, to describe an analogous gravitomagnetic field. They are well established by the theory, and experimental tests form ongoing research. ==== Classical laws ==== Kepler's laws, though originally discovered from planetary observations (also due to Tycho Brahe), are true for any central forces. === Thermodynamics === Newton's law of cooling Fourier's law Ideal gas law, combines a number of separately developed gas laws; Boyle's law Charles's law Gay-Lussac's law Avogadro's law, into one now improved by other equations of state Dalton's law (of partial pressures) Boltzmann equation Carnot's theorem Kopp's law === Electromagnetism === Maxwell's equations give the time-evolution of the electric and magnetic fields due to


id: scientific-law-20260505-4
file: data/en.wikipedia.org/wiki/Scientific_law-4.md
category: reference
title: Scientific law
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_law
date_saved: 2026-05-05T03:45:43.771670+00:00
instance: kb-cron
parent: scientific-law-20260505-0
summary:
In equilibrium, molecules exist in mixture defined by the transformations possible on the timescale of the equilibrium, and are in a ratio defined by the intrinsic energy of the molecules—the lower the intrinsic energy, the more abundant the molecule. Le Chatelier's principle states that the system opposes changes in conditions from equilibrium states, i.e. there is an opposition to change the state of an equilibrium reaction. Transforming one structure to another requires the input of energy to cross an energy barrier; this can come from the intrinsic energy of the molecules themselves, or from an external source which will generally accelerate transformations. The higher the energy barrier, the slower the transformation occurs. There is a hypothetical intermediate, or transition structure, that corresponds to the structure at the top of the energy barrier. The Hammond–Leffler postulate states that this structure looks most similar to the product or starting material which has intrinsic energy closest to that of the energy barrier. Stabilizing this hypothetical intermediate through chemical interaction is one way to achieve catalysis. All chemical processes are reversible (law of microscopic reversibility) although some processes have such an energy bias, they are essentially irreversible. The reaction rate has the mathematical parameter


id: scientific-law-20260505-5
file: data/en.wikipedia.org/wiki/Scientific_law-5.md
category: reference
title: Scientific law
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_law
date_saved: 2026-05-05T03:45:43.771670+00:00
instance: kb-cron
parent: scientific-law-20260505-0
summary:
In Europe, systematic theorizing about nature (physis) began with the early Greek philosophers and scientists and continued into the Hellenistic and Roman imperial periods, during which times the intellectual influence of Roman law increasingly became paramount.The formula "law of nature" first appears as "a live metaphor" favored by Latin poets Lucretius, Virgil, Ovid, Manilius, in time gaining a firm theoretical presence in the prose treatises of Seneca and Pliny. Why this Roman origin? According to [historian and classicist Daryn] Lehoux's persuasive narrative, the idea was made possible by the pivotal role of codified law and forensic argument in Roman life and culture. For the Romans ... the place par excellence where ethics, law, nature, religion and politics overlap is the law court. When we read Seneca's Natural Questions, and watch again and again just how he applies standards of evidence, witness evaluation, argument and proof, we can recognize that we are reading one of the great Roman rhetoricians of the age, thoroughly immersed in forensic method. And not Seneca alone. Legal models of scientific judgment turn up all over the place, and for example prove equally integral to Ptolemy's approach to verification, where the mind is assigned the role of


id: scientific-priority-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_priority-0.md
category: reference
title: Scientific priority
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_priority
date_saved: 2026-05-05T03:45:44.912301+00:00
instance: kb-cron
parent: scientific-priority-20260505-0
summary:
In science, priority is the credit given to the individual or group of individuals who first made the discovery or proposed the theory. Fame and honours usually go to the first person or group to publish a new finding, even if several researchers arrived at the same conclusion independently and at the same time. Thus, between two or more independent discoverers, the first to publish is the legitimate winner. Hence, the tradition is often referred to as the priority rule, the procedure of which can be summed up in the phrase "publish or perish", because there are generally no prizes for second place in science academia. In a way, the race to be first inspires risk-taking that can lead to scientific breakthroughs which is beneficial to the society (such as discovery of malaria transmission, DNA, HIV, etc.). On the other hand, it can create unhealthy competition and incentives to publish low-quality findings (e.g., quantity over quality or committing scientific misconduct), which can lead to an unreliable published literature and harm scientific progress. == Priority disputes == Priority becomes a difficult issue usually in the context of priority disputes, where the priority for a given theory, understanding, or discovery comes into


id: scientific-protocol-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_protocol-0.md
category: reference
title: Scientific protocol
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_protocol
date_saved: 2026-05-05T03:45:46.143301+00:00
instance: kb-cron
parent: scientific-protocol-20260505-0
summary:
In natural and social science research, a protocol is most commonly a predefined procedural method in the design and implementation of an experiment. Protocols are written whenever it is desirable to standardize a laboratory method to ensure successful replication of results by others in the same laboratory or by other laboratories. Additionally, and by extension, protocols have the advantage of facilitating the assessment of experimental results through peer review. In addition to detailed procedures, equipment, and instruments, protocols will also contain study objectives, reasoning for experimental design, reasoning for chosen sample sizes, safety precautions, and how results were calculated and reported, including statistical analysis and any rules for predefining and documenting excluded data to avoid bias. Similarly, a protocol may refer to the procedural methods of health organizations, commercial laboratories, manufacturing plants, etc. to ensure their activities (e.g., blood testing at a hospital, testing of certified reference materials at a calibration laboratory, and manufacturing of transmission gears at a facility) are consistent to a specific standard, encouraging safe use and accurate results. Finally, in the field of social science, a protocol may also refer to a "descriptive record" of observed events or a "sequence of behavior" of one or more


id: scientific-study-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_study-0.md
category: reference
title: Scientific study
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_study
date_saved: 2026-05-05T03:45:47.413689+00:00
instance: kb-cron
parent: scientific-study-20260505-0
summary:
Scientific study is a creative action to increase knowledge by systematically collecting, interpreting, and evaluating data. According to the hypothetico-deductive paradigm, it should encompass: The contextualization of the problem; A hypothesis for explaining the problem considering existing theoretical approaches; A verification of the hypotheses by an experiment; Analysis of the test outcome. Scientific study involves scientific theory, scientific method, scientific models, experiments and physical situations. It may refer to: Scientific method, a body of techniques for investigating phenomena, based on empirical or measurable evidence that is subject to the principles of logic and reasoning Observational study, draws inferences about the possible effect of a treatment on subjects, where the assignment of subjects into a treated group versus a control group is outside the control of the investigator Randomized controlled trial, a type of scientific experiment, often in the medical field, where the people being studied are randomly allocated one of the different treatments Science, a systematic enterprise that builds and organizes knowledge in the form of testable explanations and predictions about the universe. Scientific learning includes testing of theories and provide a basis for scientific knowledge. == History == Aristotle is believed to be the first to begin the study


id: scientific-temper-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_temper-0.md
category: reference
title: Scientific temper
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_temper
date_saved: 2026-05-05T03:45:48.591816+00:00
instance: kb-cron
parent: scientific-temper-20260505-0
summary:
The term scientific temper is broadly defined as "a modest open-minded temper—develop new light, new knowledge, new experiments, even when their results are unfavourable to preconceived opinions and long-cherished theories." It is a way of life (defined in this context as an individual and social process of thinking and acting) which uses the scientific method and which may, consequently, include questioning, observing physical reality, testing, hypothesizing, analyzing, and communicating (not necessarily in that order). Discussion, argument and analysis are vital parts of scientific temper. It aims to inculcate the values of scientific thinking, appreciate scientific development, and drive away superstition, religious bigotry, and all forms of pseudo-science. == Development of Scientific Temperament in World == Scientific temper as a notion existed for a long time, and the origin of the term is unknown. The exact terminology became frequently used in the mid-19th century. A Jesuit scholar Thomas Aloysius Hughes gave a short definition in 1893, saying, "A scientific temper... means a scrupulous and rigid exactness... [which] is the outcome of exact science." In his Conway Memorial Lecture in 1922, Bertrand Russell used the example of Albert Einstein to explain the meaning of scientific temper:We have had in recent years a


id: scientific-theory-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_theory-0.md
category: reference
title: Scientific theory
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_theory
date_saved: 2026-05-05T03:45:49.802572+00:00
instance: kb-cron
parent: scientific-theory-20260505-0
summary:
A scientific theory is an explanation of an aspect of the natural world that can be or that has been repeatedly tested and has corroborating evidence in accordance with the scientific method, using accepted protocols of observation, measurement, and evaluation of results. Where possible, theories are tested under controlled conditions in an experiment. In circumstances not amenable to experimental testing, theories are evaluated through principles of abductive reasoning. Established scientific theories have withstood rigorous scrutiny and embody scientific knowledge. A scientific theory differs from a scientific fact: a fact is an observation, while a theory connects and explains multiple observations. Furthermore, a theory is expected to make predictions which could be confirmed or refuted with additional observations. Stephen Jay Gould wrote that: "...facts and theories are different things, not rungs in a hierarchy of increasing certainty. Facts are the world's data. Theories are structures of ideas that explain and interpret facts." A theory differs from a scientific law in that a law is an empirical description of a relationship between facts and/or other laws. For example, Newton's Law of Gravity is a mathematical equation that can be used to predict the attraction between bodies, but it is not a theory


id: scientific-theory-20260505-1
file: data/en.wikipedia.org/wiki/Scientific_theory-1.md
category: reference
title: Scientific theory
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_theory
date_saved: 2026-05-05T03:45:49.802572+00:00
instance: kb-cron
parent: scientific-theory-20260505-0
summary:
It can be subjected to minor adaptations to account for new data that do not fit it perfectly, as they are discovered, thus increasing its predictive capability over time. It is among the most parsimonious explanations, economical in the use of proposed entities or explanatory steps as per Occam's razor. This is because for each accepted explanation of a phenomenon, there may be an extremely large, perhaps even incomprehensible, number of possible and more complex alternatives, because one can always burden failing explanations with ad hoc hypotheses to prevent them from being falsified; therefore, simpler theories are preferable to more complex ones because they are more testable. === Definitions from scientific organizations === The United States National Academy of Sciences defines scientific theories as follows: The formal scientific definition of theory is quite different from the everyday meaning of the word. It refers to a comprehensive explanation of some aspect of nature that is supported by a vast body of evidence. Many scientific theories are so well established that no new evidence is likely to alter them substantially. For example, no new evidence will demonstrate that the Earth does not orbit around the Sun (heliocentric theory), or that living things


id: scientific-theory-20260505-2
file: data/en.wikipedia.org/wiki/Scientific_theory-2.md
category: reference
title: Scientific theory
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_theory
date_saved: 2026-05-05T03:45:49.802572+00:00
instance: kb-cron
parent: scientific-theory-20260505-0
summary:
== Modification and improvement == If experimental results contrary to a theory's predictions are observed, scientists first evaluate whether the experimental design was sound, and if so they confirm the results by independent replication. A search for potential improvements to the theory then begins. Solutions may require minor or major changes to the theory, or none at all if a satisfactory explanation is found within the theory's existing framework. Over time, as successive modifications build on top of each other, theories consistently improve and greater predictive accuracy is achieved. Since each new version of a theory (or a completely new theory) must have more predictive and explanatory power than the last, scientific knowledge consistently becomes more accurate over time. If modifications to the theory or other explanations seem to be insufficient to account for the new results, then a new theory may be required. Since scientific knowledge is usually durable, this occurs much less commonly than modification. Furthermore, until such a theory is proposed and accepted, the previous theory will be retained. This is because it is still the best available explanation for many other phenomena, as verified by its predictive power in other contexts. For example, it has been


id: scientific-theory-20260505-3
file: data/en.wikipedia.org/wiki/Scientific_theory-3.md
category: reference
title: Scientific theory
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_theory
date_saved: 2026-05-05T03:45:49.802572+00:00
instance: kb-cron
parent: scientific-theory-20260505-0
summary:
=== Theories and facts === A scientific theory does not turn into a fact. Scientific facts are observations that theories organize and explain. As new facts appear, a theory may be revised or new theories may emerge that encompass these additional facts. While American vernacular speech uses "theory" as similar to a "guess" in opposition to a "fact", in science the word "theory" means a model that is expected to explain a wide range of facts. == About theories == === Theories as axioms === The logical positivists thought of scientific theories as statements in a formal language. First-order logic is an example of a formal language. The logical positivists envisaged a similar scientific language. In addition to scientific theories, the language also included observation sentences ("the sun rises in the east"), definitions, and mathematical statements. The phenomena explained by the theories, if they could not be directly observed by the senses (for example, atoms and radio waves), were treated as theoretical concepts. In this view, theories function as axioms: predicted observations are derived from the theories much like theorems are derived in Euclidean geometry. However, the predictions are then tested against reality to verify the predictions, and the "axioms"


id: scientific-theory-20260505-4
file: data/en.wikipedia.org/wiki/Scientific_theory-4.md
category: reference
title: Scientific theory
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_theory
date_saved: 2026-05-05T03:45:49.802572+00:00
instance: kb-cron
parent: scientific-theory-20260505-0
summary:
...it is incorrect to speak of an assumption as either true or false, since there is no way of proving it to be either (If there were, it would no longer be an assumption). It is better to consider assumptions as either useful or useless, depending on whether deductions made from them correspond to reality...Since we must start somewhere, we must have assumptions, but at least let us have as few assumptions as possible. Certain assumptions are necessary for all empirical claims (e.g. the assumption that reality exists). However, theories do not generally make assumptions in the conventional sense (statements accepted without evidence). While assumptions are often incorporated during the formation of new theories, these are either supported by evidence (such as from previously existing theories) or the evidence is produced in the course of validating the theory. This may be as simple as observing that the theory makes accurate predictions, which is evidence that any assumptions made at the outset are correct or approximately correct under the conditions tested. Conventional assumptions, without evidence, may be used if the theory is only intended to apply when the assumption is valid (or approximately valid). For example, the special theory of relativity


id: scientific-theory-20260505-5
file: data/en.wikipedia.org/wiki/Scientific_theory-5.md
category: reference
title: Scientific theory
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_theory
date_saved: 2026-05-05T03:45:49.802572+00:00
instance: kb-cron
parent: scientific-theory-20260505-0
summary:
It is easy to obtain confirmations, or verifications, for nearly every theory—if we look for confirmations. Confirmations should count only if they are the result of risky predictions; that is to say, if, unenlightened by the theory in question, we should have expected an event which was incompatible with the theory—an event which would have refuted the theory. Every "good" scientific theory is a prohibition: it forbids certain things from happening. The more a theory forbids, the better it is. A theory which is not refutable by any conceivable event is non-scientific. Irrefutability is not a virtue of a theory (as people often think) but a vice. Every genuine test of a theory is an attempt to falsify it or to refute it. Testability is falsifiability; but there are degrees of testability: some theories are more testable, more exposed to refutation, than others; they take, as it were, greater risks. Confirming evidence should not count except when it is the result of a genuine test of the theory, and this means that it can be presented as a serious but unsuccessful attempt to falsify the theory. (I now speak in such cases of "corroborating evidence".) Some genuinely testable theories, when


id: scientific-theory-20260505-6
file: data/en.wikipedia.org/wiki/Scientific_theory-6.md
category: reference
title: Scientific theory
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_theory
date_saved: 2026-05-05T03:45:49.802572+00:00
instance: kb-cron
parent: scientific-theory-20260505-0
summary:
A theory is something other than myself. It may be set out on paper as a system of rules, and it is the more truly a theory the more completely it can be put down in such terms. Mathematical theory reaches the highest perfection in this respect. But even a geographical map fully embodies in itself a set of strict rules for finding one's way through a region of otherwise uncharted experience. Indeed, all theory may be regarded as a kind of map extended over space and time. A scientific theory can also be thought of as a book that captures the fundamental information about the world, a book that must be researched, written, and shared. In 1623, Galileo Galilei wrote: Philosophy [i.e. physics] is written in this grand book—I mean the universe—which stands continually open to our gaze, but it cannot be understood unless one first learns to comprehend the language and interpret the characters in which it is written. It is written in the language of mathematics, and its characters are triangles, circles, and other geometrical figures, without which it is humanly impossible to understand a single word of it; without these, one is wandering around in a


id: scientism-20260505-0
file: data/en.wikipedia.org/wiki/Scientism-0.md
category: reference
title: Scientism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientism
date_saved: 2026-05-05T03:45:51.099471+00:00
instance: kb-cron
parent: scientism-20260505-0
summary:
Scientism is the belief that science and the scientific method are the best or only way to render truth about the world and reality. While the term was defined originally to mean "methods and attitudes typical of or attributed to natural scientists", some scholars, as well as political and religious leaders, have also adopted it as a pejorative term with the meaning "an exaggerated trust in the efficacy of the methods of natural science applied to all areas of investigation (as in philosophy, the social sciences, and the humanities)". == Overview == Francis Bacon has been viewed by some scholars as an early proponent of scientism, but this is a modern assertion as Bacon was a devout Anglican, writing in his Essays, "a little philosophy inclineth man's mind to atheism, but depth in philosophy bringeth men's minds about to religion." With respect to the philosophy of science, the term scientism frequently implies a critique of the more extreme expressions of logical positivism and has been used by social scientists such as Friedrich Hayek, philosophers of science such as Karl Popper, and philosophers such as Mary Midgley, the later Hilary Putnam, and Tzvetan Todorov to describe (for example) the dogmatic endorsement


id: scientism-20260505-1
file: data/en.wikipedia.org/wiki/Scientism-1.md
category: reference
title: Scientism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientism
date_saved: 2026-05-05T03:45:51.099471+00:00
instance: kb-cron
parent: scientism-20260505-0
summary:
It is used to criticize a totalizing opinion of science as if it were capable of describing all reality and knowledge, or as if it were the only true method to acquire knowledge about reality and the nature of things; It is used, often pejoratively, to denote violations by which the theories and methods of one (scientific) discipline are applied inappropriately to another (scientific or non-scientific) discipline and its domain. An example of this second usage is to term as scientism any attempt to claim science as the only or primary source of human values (a traditional domain of ethics) or as the source of meaning and purpose (a traditional domain of religion and related worldviews). The term scientism was popularized by F. A. Hayek, who defined it in 1942 as the "slavish imitation of the method and language of Science". Mathematician Alexander Grothendieck, in his 1971 essay "The New Universal Church", characterized scientism as a religion-like ideology that advocates scientific reductionism, scientific authoritarianism, political technocracy and technological salvation, while denying the epistemological validity of feelings and experiences such as love, emotion, beauty and fulfillment. He predicted that "in coming years, the chief political dividing line will fall less and


id: scientism-20260505-2
file: data/en.wikipedia.org/wiki/Scientism-2.md
category: reference
title: Scientism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientism
date_saved: 2026-05-05T03:45:51.099471+00:00
instance: kb-cron
parent: scientism-20260505-0
summary:
== Relevance to debates about science and religion == Both religious and non-religious scholars have applied the term scientism to individuals associated with New Atheism. Theologian John Haught argued that philosopher Daniel Dennett and other New Atheists subscribe to a belief system of scientific naturalism, which includes the dogma that "only nature, including humans and our creations, is real: that God does not exist; and that science alone can give us complete and reliable knowledge of reality." Haught argued that this belief system is self-refuting since it requires its adherents to assent to beliefs that violate its own stated requirements for knowledge. Christian philosopher Peter Williams argued in 2013 that it is only by conflating science with scientism that New Atheists feel qualified to "pontificate on metaphysical issues". Daniel Dennett responded to religious criticism of his 2006 book Breaking the Spell: Religion as a Natural Phenomenon by saying that accusations of scientism "[are] an all-purpose, wild-card smear ... When someone puts forward a scientific theory that [religious critics] really don't like, they just try to discredit it as 'scientism'. But when it comes to facts, and explanations of facts, science is the only game in town". Non-religious scholars have also


id: scientism-20260505-3
file: data/en.wikipedia.org/wiki/Scientism-3.md
category: reference
title: Scientism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientism
date_saved: 2026-05-05T03:45:51.099471+00:00
instance: kb-cron
parent: scientism-20260505-0
summary:
Thomas M. Lessl argued that religious themes persist in what he terms scientism, the public rhetoric of science. There are two methods of describing this idea of scientism: the epistemological method (the assumption that the scientific method trumps other ways of knowing) and the ontological method (that the rational mind represents the world and both operate in knowable ways). According to Lessl, the ontological method is an attempt to "resolve the conflict between rationalism and skepticism". Lessl also argued that without scientism, there would not be a scientific culture. == Rationalization and modernity == In the introduction to his collected works on the sociology of religion, Max Weber asked why "the scientific, the artistic, the political, or the economic development [elsewhere] ... did not enter upon that path of rationalization which is peculiar to the Occident?" According to the German social theorist Jürgen Habermas, "For Weber, the intrinsic (that is, not merely contingent) relationship between modernity and what he called 'Occidental rationalism' was still self-evident." Weber described a process of rationalisation, disenchantment and the "disintegration of religious world views" that resulted in modern secular societies and capitalism. "Modernization" was introduced as a technical term only in the 1950s. It is


id: secondary-research-20260505-0
file: data/en.wikipedia.org/wiki/Secondary_research-0.md
category: reference
title: Secondary research
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Secondary_research
date_saved: 2026-05-05T03:45:52.254825+00:00
instance: kb-cron
parent: secondary-research-20260505-0
summary:
Secondary research involves the summary, collation and/or synthesis of existing research. Secondary research is contrasted with primary research in that primary research involves the generation of data, whereas secondary research uses primary research sources as a source of data for analysis. A notable marker of primary research is the inclusion of a "methods" section, where the authors describe how the data was generated. Common examples of secondary research include textbooks, encyclopedias, news articles, review articles, and meta analyses. When conducting secondary research, authors may draw data from published academic papers, government documents, statistical databases, and historical records. == Fields == The term is widely used in fields such as history, legal research, market research, and Wikipedia editing. The principal methodology in health secondary research is the systematic review, commonly using meta-analytic statistical techniques. Other methods of synthesis, like realist reviews and meta-narrative reviews, have been developed in the 21st century. Secondary market research includes the reuse by a second party of any data collected from a first party such as telephone interviews or surveys. Secondary market research can be broken up into two categories: information from internal sources such as an agency or company, and information from external sources held


id: selection-bias-20260505-0
file: data/en.wikipedia.org/wiki/Selection_bias-0.md
category: reference
title: Selection bias
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Selection_bias
date_saved: 2026-05-05T03:45:53.377239+00:00
instance: kb-cron
parent: selection-bias-20260505-0
summary:
Selection bias is the bias introduced by the selection of individuals, groups, or data for analysis in such a way that the association between exposure and outcome among those selected for analysis differs from the association among those eligible. It typically occurs when researchers condition on a factor that is influenced both by the exposure and the outcome (or their causes), creating a false association between them. Selection bias encompasses several forms of bias, including differential loss-to-follow-up, incidence–prevalence bias, volunteer bias, healthy-worker bias, and nonresponse bias. == Types of bias == === Sampling bias === Sampling bias is systematic error due to a non-random sample of a population, causing some members of the population to be less likely to be included than others, resulting in a biased sample, defined as a statistical sample of a population (or non-human factors) in which all participants are not equally balanced or objectively represented. It is mostly classified as a subtype of selection bias, sometimes specifically termed sample selection bias, but some classify it as a separate type of bias. A distinction of sampling bias (albeit not a universally accepted one) is that it undermines the external validity of a test (the ability of


id: selection-bias-20260505-1
file: data/en.wikipedia.org/wiki/Selection_bias-1.md
category: reference
title: Selection bias
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Selection_bias
date_saved: 2026-05-05T03:45:53.377239+00:00
instance: kb-cron
parent: selection-bias-20260505-0
summary:
=== Observer selection === Philosopher Nick Bostrom has argued that data are filtered not only by study design and measurement, but by the necessary precondition that there has to be someone doing a study. In situations where the existence of the observer or the study is correlated with the data, observation selection effects occur, and anthropic reasoning is required. An example is the past impact event record of Earth: if large impacts cause mass extinctions and ecological disruptions precluding the evolution of intelligent observers for long periods, no one will observe any evidence of large impacts in the recent past (since they would have prevented intelligent observers from evolving). Hence there is a potential bias in the impact record of Earth. Astronomical existential risks might similarly be underestimated due to selection bias, and an anthropic correction has to be introduced. === Volunteer bias === Self-selection bias or a volunteer bias in studies offer further threats to the validity of a study as these participants may have intrinsically different characteristics from the target population of the study. Studies have shown that volunteers tend to come from a higher social standing than from a lower socio-economic background. Furthermore, another study shows that


