Scrape wikipedia-science: 711 new, 19 updated, 752 total (kb-cron)

data/en.wikipedia.org/wiki/Experimenter's_regress-0.md

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+---
+title: "Experimenter's regress"
+chunk: 1/1
+source: "https://en.wikipedia.org/wiki/Experimenter's_regress"
+category: "reference"
+tags: "science, encyclopedia"
+date_saved: "2026-05-05T03:15:43.003414+00:00"
+instance: "kb-cron"
+---
+
+In science, experimenter's regress refers to a loop of dependence between theory and evidence. In order to judge whether a new piece of evidence is correct we rely on theory-based predictions, and to judge the value of competing theories we rely on existing evidence. Cognitive bias affects experiments, and experiments determine which theory is valid. This issue is particularly important in new fields of science where there is no consensus regarding the values of various competing theories, and where the extent of experimental errors is not well known. 
+If experimenter's regress acts a positive feedback system, it can be a source of pathological science. An experimenter's strong belief in a new theory produces confirmation bias, and any biased evidence they obtain then strengthens their belief in that particular theory. Neither individual researchers nor entire scientific communities are immune to this effect: see N-rays and polywater.
+Experimenter's regress is a typical relativistic phenomenon in the Empirical Programme of Relativism (EPOR). EPOR is very much concerned with a focus on social interactions, by looking at particular (local) cases and controversial issues in the context in which they happen. In EPOR, all scientific knowledge is perceived to be socially constructed and is thus "not given by nature".
+In his article Son of seven sexes: The Social Destruction of a Physical Phenomenon, Harry Collins argued that scientific experiments are subject to what he calls "experimenter's regress". The outcome of a phenomenon that is studied for the first time is always uncertain and judgment in these situations, about what matters, requires considerable experience, tacit and practical knowledge. When a scientist runs an experiment, and the experiment yields a result, they can never be sure whether this is the result which they had expected. The result looks good because they know that their experimental protocol was correct; or the result looks wrong, and therefore there must be something wrong with their experimental protocol. The scientist, in other words, has to get the right answer in order to know that the experiment is working, or know that the experiment is working to get the right answer.
+In his book Changing Order  Collins  defines the paradox of Experimenter's regress as follows:
+
+This is a paradox which arises for those who want to use replication as a test of the truth of scientific knowledge claims. The problem is that, since experimentation is a matter of skilful practice, it can never be clear whether a second experiment has been done sufficiently well to count as a check on the results of a first. Some further test is needed to test the quality of the experiment - and so forth.
+Experimenter's regression occurs at the "research frontier" where the outcome of research is uncertain, for the scientist is dealing with "novel phenomena". Collins puts it this way: "usually, successful practice of an experimental skill is evident in a successful outcome to an experiment, but where the detection of a novel phenomenon is in question, it is not clear what should count as a 'successful outcome' – detection or non-detection of the phenomenon" (Collins 1981: 34). In new fields of research where no paradigm has yet evolved and where no consensus exists as what counts as proper research, experimenter's regress is a problem that often occurs. Also, in situations where there is much controversy over a discovery or claim due to opposing interests, dissenters will often question experimental evidence that founds a theory.
+Because, for Collins, all scientific knowledge is socially constructed, and there are no purely cognitive reasons or objective criteria that determine whether a claim is valid or not. The regress must be broken by "social negotiation" between scientists in the respective field. In the case of Gravitational Radiation, Collins notices that Weber, the scientist who is said to have discovered the phenomenon, could refute all the critique and had "a technical answer for every other point" but he was not able to convince other scientists and, in the end, he was not taken seriously anymore.
+The problems that come with "experimenter's regress" can never be fully avoided because scientific outcomes in EPOR are seen as negotiable and socially constructed. Acceptance of claims boils down to the persuasion of other people in the community. Experimenter's regress can always become a problem in a world where "the natural world in no way constrains what is believed to be". Moreover, it is difficult to falsify a claim by replicating an experiment; aside from the practical issues of time, money, access to facilities, etc., an experimental outcome may depend on precise conditions, or tacit knowledge (i.e. unarticulated knowledge) that was not included in the published experimental methods. Tacit knowledge can never be fully articulated or translated into a set of rules.
+Some commentators have argued that Collins's "experimenter's regress" is foreshadowed by Sextus Empiricus' argument that "if we shall judge the intellects by the senses, and the senses by the intellect, this involves circular reasoning as much as it is required that the intellects should be judged first in order that the intellects may be tested [hence] we possess no means by which to judge objects" (quoted after Godin & Gingras 2002: 140). Others have extended Collins's argument to the cases of theoretical practice ("theoretician's regress"; Kennefick 2000) and computer simulation studies ("Simulationist's regress"; Gelfert 2011; Tolk 2017).
+
+
+== See also ==
+Experimenter's bias
+
+
+== References ==
+
+
+== External links ==
+Experimenter's Regress on The Stanford Encyclopedia of Philosophy
+Brown, Matthew J. (2008):  "Inquiry, Evidence, and Experiment: The "Experimenter's Regress" Dissolved", abstract, with link to full text.

data/en.wikipedia.org/wiki/Experimentum_crucis-0.md

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+title: "Experimentum crucis"
+chunk: 1/1
+source: "https://en.wikipedia.org/wiki/Experimentum_crucis"
+category: "reference"
+tags: "science, encyclopedia"
+date_saved: "2026-05-05T03:15:44.257402+00:00"
+instance: "kb-cron"
+---
+
+In science, an experimentum crucis (English: crucial experiment or critical experiment) is an experiment capable of decisively determining whether or not a particular hypothesis or theory is superior to all others whose acceptance is currently widespread in the scientific community. In particular, such an experiment—if true—must typically be able to produce a result that rules out all other hypotheses or theories, thereby demonstrating that under the conditions of the experiment (i.e., under the same external circumstances and for the same "input variables" within the experiment), those hypotheses and theories are proven false but the experimenter's hypothesis is not ruled out.
+An opposite view, rejecting the decisive value of the experimentum crucis in choosing one hypothesis or theory over its rivals, is the Duhem–Quine thesis.
+
+
+== History ==
+Francis Bacon in his Novum Organum first described the concept of a situation in which one theory but not others would hold true, using the name instantia crucis ("crucial instance"). The phrase experimentum crucis, denoting the deliberate creation of such a situation for the purpose of testing the rival theories, was later coined by Robert Hooke and then famously used by Isaac Newton and Robert Boyle.
+The production of such an experiment is considered necessary for a particular hypothesis or theory to be considered an established part of the body of scientific knowledge. It is not unusual in the history of science for theories to be developed fully before producing a critical experiment. A given theory which is in accordance with known experiment but which has not yet produced a critical experiment is typically considered worthy of exploration in order to discover such an experimental test.
+
+
+== Examples ==
+Robert Boyle was the first person to hail an experiment as experimentum crucis when he referred to the famous mercury barometer experiment on Puy-de-Dome in 1648. This experiment settled the question: Was there some natural resistance to the creation of an apparently empty space at the top of the tube, or was the height of the mercury determined solely by the weight of the air?
+In his Philosophiæ Naturalis Principia Mathematica, Isaac Newton (1687) presents a disproof of Descartes' vortex theory of the motion of the planets. In his Opticks, Newton describes an optical experimentum crucis in the First Book, Part I, Proposition II, Theorem II, Experiment 6, to prove that sunlight consists of rays that differ in their index of refraction.
+
+A 19th-century example was the prediction by Poisson, based on Fresnel's mathematical analysis, that the wave theory of light predicted a bright spot in the center of the shadow of a perfectly circular object, a result that could not be explained by the (then current) particle theory of light. An experiment by François Arago showed the existence of this effect, now called the Arago spot, or "Poisson's bright spot", which led to the acceptance of the wave theory.
+A famous example in the 20th century of an experimentum crucis was the expedition led by Arthur Eddington to Principe Island in Africa in 1919 to record the positions of stars around the Sun during a solar eclipse (see Eddington experiment). The observation of star positions confirmed predictions of gravitational lensing made by Albert Einstein in the general theory of relativity published in 1915. Eddington's observations were considered to be the first solid evidence in favor of Einstein's theory.
+In some cases, a proposed theory can account for existing anomalous experimental results for which no other existing theory can furnish an explanation. An example would be the ability of the quantum hypothesis, proposed by Max Planck in 1900, to account for the observed black-body spectrum, an experimental result that the existing classical Rayleigh–Jeans law could not predict. Such cases are not considered strong enough to fully establish a new theory, however, and in the case of quantum mechanics, it took the confirmation of the theory through new predictions for the theory to gain full acceptance.
+
+
+=== DNA, experimentum crucis ===
+See §Context for crucial experiment in the discovery of the §structure of DNA, and §List of experiments in biology
+In the discovery of the significance of the structure of DNA, the fact that DNA was a double helix enabled the discoverers, Francis Crick and James Watson, to suggest that one strand of the double helix could serve as the template for the second strand, as the second strand was being duplicated. This explained the secret of life, how the structure of DNA could serve as the mechanism for the gene (the genetic code), in which four nucleotides serve to encode the sequence of enzymes needed to catalyze the production of macromolecules in the cell, and which led to its application in synthetic biology, in genetic engineering, in forensics, genetic testing, genomics and pharmaceuticals, among other industries.
+
+
+=== Tanis fossil site ===
+
+In the 21st century, the discovery of the Tanis fossil site, a killing field in the Hell Creek formation of North Dakota, proved that the K-T boundary (now known as the KPg, or the Cretaceous–Paleogene extinction event) was the same event (the Chicxulub impact) which killed off the dinosaurs. This impact event was previously hypothesized from the global existence of iridium deposits 
+(a rare element on Earth). In this case, the existence of a microtektite layer raining down upon the multiple intermixed species (including a Triceratops) which were found at the site (the Tanis Konservat-Lagerstätte) served as the conclusive witness,  as cited in Science Daily. Based on the dating of the Tanis, the event occurred 65.76 million years ago  (± 0.15 My).
+
+
+=== Theory of Experimentum Crucis ===
+There's an emerging scholarship extending understanding and evaluation of experiments that fit into this category. J. A. Lohne tracks the development of the idea from Francis Bacon's 1620 Instantie Crucis through the various prism optics experiments and discussions of 1722.
+An early indicator of a theory of Experimentum Crucis appears in John Locke's Doctrine of Abstraction.
+Lorne Falkenstein, reviewing  Van Cleve expands the discussion  of Experimentum crucis to the more general philosophical realm of Property dualism.
+
+
+== See also ==
+Contraposition in logic, the formal basis of an experimentum crucis
+Cross-validation (disambiguation)
+Pierre Duhem § Philosophy of science
+Falsifiability
+Material conditional
+Q.E.D.
+Scientific method
+Smoking gun
+Therefore sign
+
+
+== Notes ==

data/en.wikipedia.org/wiki/Expert_elicitation-0.md

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+---
+title: "Expert elicitation"
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+source: "https://en.wikipedia.org/wiki/Expert_elicitation"
+category: "reference"
+tags: "science, encyclopedia"
+date_saved: "2026-05-05T03:15:45.403756+00:00"
+instance: "kb-cron"
+---
+
+In science, engineering, and research, expert elicitation is the synthesis of opinions of authorities of a subject where there is uncertainty due to insufficient data or when such data is unattainable because of physical constraints or lack of resources. Expert elicitation is essentially a scientific consensus methodology. It is often used in the study of rare events. Expert elicitation allows for parametrization, an "educated guess", for the respective topic under study. Expert elicitation generally helps quantify uncertainty.
+Expert elicitation tends to be multidisciplinary as well as interdisciplinary, with practically universal applicability, and is used in a broad range of fields. Prominent recent expert elicitation applications include climate change, modeling seismic hazard and damage, association of tornado damage to wind speed in developing the Enhanced Fujita scale, risk analysis for nuclear waste storage.
+In performing expert elicitation certain factors need to be taken into consideration. The topic must be one for which there are people who have predictive expertise. Furthermore, the objective should be to obtain an experts' carefully considered judgment based on a systematic consideration of all relevant evidence. For this reason one should take care to adopt strategies designed to help the expert being interviewed to avoid overlooking relevant evidence. Additionally, vocabulary used should face intense scrutiny; qualitative uncertainty words such as "likely" and "unlikely" are not sufficient and can lead to confusion. Such words can mean very different things to different people, or to the same people in different situations.
+
+
+== See also ==
+Applied science
+Bayesian probability
+
+
+== References ==
+
+
+== Bibliography ==
+Apostolakis, G., 7 December 1990: The concept of probability in safety assessments of technological systems. Science, 250 (4986): 1359–1364. doi:10.1126/science.2255906
+Arkes, Hal R., Jeryl L. Mumpower, and Thomas R. Stewart, 24 January 1997: Combining Expert Opinions. Science, 275: 461–465. doi:10.1126/science.275.5299.461e
+Boissonnade, A., Hossain, Q., Kimbell, J., Mensing, R., and Savy, J., 2000: Development of a probabilistic tornado wind hazard model for the Continental United States, UCRL-ID-140922 Vol. I, Lawrence Livermore National Laboratory, Livermore, CA, 131pp.
+Booker, Jane M.; Meyer, Mary A. (2001), Eliciting and Analyzing Expert Judgment: A Practical Guide, Society for Industrial and Applied Mathematics
+Kerr, Richard A., 8 November 1996: Risk Assessment: A New Way to Ask the Experts: Rating Radioactive Waste Risks. Science, 274 (5289): 913–914. doi:10.1126/science.274.5289.913
+SSHAC, 1997: Recommendations for probabilistic seismic hazard analysis: guidelines on uncertainty and use of experts, NUREG/CR-6372, UCRL-ID-122160, Vol. I, Lawrence Livermore National Laboratory, Livermore, CA, 131 pp.

data/en.wikipedia.org/wiki/Extended_peer_community-0.md

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+---
+title: "Extended peer community"
+chunk: 1/1
+source: "https://en.wikipedia.org/wiki/Extended_peer_community"
+category: "reference"
+tags: "science, encyclopedia"
+date_saved: "2026-05-05T03:15:46.795989+00:00"
+instance: "kb-cron"
+---
+
+The concept of Extended peer community belongs to the field of Sociology of science, and in particular the use of science in the solution of social, political or ecological problems. It was first introduced by in the 1990s by Silvio Funtowicz and Jerome R. Ravetz. in the context of what would become Post-normal science.
+An Extended peer community is intended by these authors as a space where both credentialed experts from different disciplines and lay stakeholders can discuss and deliberate.
+
+
+== Content ==
+An Extended peer community is intended by its creators as an arrangement at the science policy interface that helps to expand and assess both the knowledge-base and the value-base of policy-making'.
+Post-normal science's extended peer community argues for two kind of extensions: first, more than one discipline is assumed to have a potential bearing on the issue being debated, thereby providing different lenses to consider the problem. Second the community is extended to lay actors, taken to be all those with stakes, or an interest, in the given issue. 
+The lay members of the community thus constituted may also take upon themselves active 'research' tasks; this has happened e.g. in the so-called 'popular epidemiology', when the official authorities have shown reluctance to perform investigations deemed necessary by the communities affected - for example - by a case of air or water pollution, and more recently ‘citizen science’. The extended community can usefully investigate the quality of the scientific assessments provided by the experts, the definition of the problem, as well as research priorities and research questions. 
+An example of extended peer community in action is offered by Brian Wynne, who discusses the Cumbrian sheep farmers' interaction with scientists and authorities, mobilizing farmers' knowledge of the relevant situation (acid upland moors retaining radioactive deposition from fallout longer than the lowland Oxfordshire meadows on which the official parameters were based).
+Extended peer communities and Post-normal Science have been suggested to tackle the debate on the policy and regulation of Large Language Models in order to encourage "inclusion of previously marginalised perspectives". 
+The concept of extended peer community was developed in the context of politicised quality controversies in science (such as 'housewife' or 'popular' epidemiology), early evidence-based medicine (the Cochrane collaboration), and the total quality management ideas of W. Edwards Deming, in particular quality circles. EPC is discussed in a special issue of the journal Science, Technology, & Human Values. For Eugene A. Rosa EPC can help charting "extended facts", meant as local knowledge, understanding, and non academic sources.
+
+
+== See also ==
+Post-normal science
+Sociology of scientific knowledge
+Technology and society
+Science studies
+Social construction of technology
+
+
+== References ==

data/en.wikipedia.org/wiki/Free_parameter-0.md

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+---
+title: "Free parameter"
+chunk: 1/1
+source: "https://en.wikipedia.org/wiki/Free_parameter"
+category: "reference"
+tags: "science, encyclopedia"
+date_saved: "2026-05-05T03:15:48.050899+00:00"
+instance: "kb-cron"
+---
+
+A free parameter is a variable in a mathematical model which cannot be predicted precisely or constrained by the model and must be estimated experimentally or theoretically. A mathematical model, theory, or conjecture is more likely to be right and less likely to be the product of wishful thinking if it relies on few free parameters and is consistent with large amounts of data.
+
+
+== See also ==
+Decision variables
+Exogenous variables
+Overfitting
+Random variables
+State variables
+
+
+== References ==

data/en.wikipedia.org/wiki/Fringe_science-0.md

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data/en.wikipedia.org/wiki/Gold_effect-0.md

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+---
+title: "Gold effect"
+chunk: 1/1
+source: "https://en.wikipedia.org/wiki/Gold_effect"
+category: "reference"
+tags: "science, encyclopedia"
+date_saved: "2026-05-05T03:15:50.630882+00:00"
+instance: "kb-cron"
+---
+
+The Gold effect is the phenomenon in which a scientific idea, particularly in medicine, is developed to the status of an accepted position within a professional body or association by the social process itself of scientific conferences, committees, and consensus building, despite not being supported by conclusive evidence. The Gold effect is used to analyze errors in public health policy and practice, such as the widespread use of cholesterol screening in the prevention of cardiovascular disease.
+
+The effect was described by Thomas Gold in 1979. The effect was reviewed by Petr Skrabanek and James McCormick in their book Follies and Fallacies in Medicine. In their book, Skrabanek and McCormick describe the Gold effect as: "At the beginning a few people arrive at a state of near belief in some idea. A meeting is held to discuss the pros and cons of the idea. More people favouring the idea than those disinterested will be present. A representative committee will be nominated to prepare a collective volume to propagate and foster interest in the idea. The totality of resulting articles based on the idea will appear to show an increasing consensus. A specialized journal will be launched. Only orthodox or near orthodox articles will pass the referees and the editor."
+The progression of the Gold effect was described by mathematician Raymond Lyttleton. According to Lyttleton, the area under the curve of a gaussian curve represents the number of people concerned with a particular subject. As the Gold effect progresses and more and more people start believing a particular idea, the gaussian curve starts to concentrate more around the center. By the end, the gaussian function will have become a delta function, representing everyone as a believer (infinite value at 0), with no non-believers.
+
+
+== References ==

data/en.wikipedia.org/wiki/Graphism_thesis-0.md

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+---
+title: "Graphism thesis"
+chunk: 1/1
+source: "https://en.wikipedia.org/wiki/Graphism_thesis"
+category: "reference"
+tags: "science, encyclopedia"
+date_saved: "2026-05-05T03:15:51.818042+00:00"
+instance: "kb-cron"
+---
+
+In the sociology of science and science and technology studies (STS), the graphism thesis is a proposition advanced by Bruno Latour that visual inscriptions—especially graphs, diagrams, and other visual representations—are central to the practice and authority of science. First articulated in Latour's 1990 essay "Visualization and Cognition: Drawing Things Together", the thesis holds that the power of scientific disciplines is closely linked to their capacity to produce, circulate, and combine visual representations of data. The thesis has been empirically tested by a number of researchers, who have found strong correlations between the level of graph use in scientific publications and the perceived "hardness" of scientific disciplines.
+
+
+== Background ==
+The graphism thesis emerged from Latour's broader theory of inscriptions in scientific practice, developed across several works including Laboratory Life (1979, with Steve Woolgar) and Science in Action (1987). In these works, Latour defined an inscription device as any apparatus or configuration that transforms a material substance into a visual display usable within a scientific text, such as a diagram, chart, photograph, map, equation, or table.
+Central to this framework is the concept of immutable mobiles (a key term in actor–network theory)—objects that can be transported across distances while retaining their form, thereby allowing scientific claims to be mobilized and compared in new contexts. Latour argued that much of what gives science its distinctive power lies not in abstract cognitive capacities or special methods of reasoning, but in the concrete practices by which scientists render phenomena into compact, transportable, and combinable visual forms. According to this view, scientific controversies are won by those who can assemble the largest number of well-aligned inscriptions in one place.
+The notion of graphism was intended by Latour to underscore the pervasiveness of visual representations throughout scientific practice, from laboratory bench work and instrument readings through to the published figures in journal articles.
+
+
+== Empirical research ==
+
+
+=== Graph use and the hierarchy of sciences ===
+The graphism thesis has been the subject of several empirical investigations using scientometric methods. In a 1984 survey of 57 scientific journals, William Cleveland found that the proportion of page space devoted to graphs (the "fractional graph area") varied widely across disciplines, ranging from 0% to 31%. Cleveland found that natural sciences journals used substantially more graphs than journals in mathematics or the social sciences, and that social science journals often presented large amounts of observational data without accompanying graphs.
+In 2000, Laurence D. Smith and colleagues extended this line of research by directly applying Latour's notion of graphism to the hierarchy of the sciences. Surveying journals in seven major scientific disciplines, they found that the use of graphs correlated "almost perfectly" with the perceived hardness of each discipline (r = 0.97). The same pattern held across ten specialty fields within psychology (r = 0.93), suggesting that the relationship between graph use and scientificity applies not only between major disciplines but also within individual fields.
+
+
+=== Non-graph visual inscriptions ===
+In a 2006 follow-up study, Darin J. Arsenault, Smith, and Edith A. Beauchamp extended the analysis beyond graphs to include non-graph illustrations (NGIs) such as photographs, conceptual diagrams, and other visual displays. Like graphs, non-graph illustrations were used more heavily in the harder sciences. Among NGI types, photographs were used most frequently in biomedical fields, while conceptual diagrams were more common in softer sciences.
+A notable finding of this study was that neither the use of tables nor the use of equations was systematically related to disciplinary hardness, suggesting that the scientificity of disciplines may be more closely related to their visuality than to their mathematization. This finding complicates the common assumption that mathematics is the primary marker of "hard" science, and instead points toward visual representation as a more reliable indicator.
+
+
+=== Additional studies ===
+Lisa A. Best, Smith, and D. Alan Stubbs conducted further research on graph use across psychology and other sciences, confirming the general pattern that visual representations serve as important tools for data analysis, interpretation, and communication in scientific disciplines. Roger Krohn also addressed the centrality of graphs in science, arguing that their use in problem-solving analysis can best be understood through an interactionist framework encompassing perception, culture, and social organization.
+Research on inscription practices has also been extended to specific disciplines including gerontology, where approximately 11 percent of page space was found to be dedicated to data presentation, with tables occupying more space than graphs.
+
+
+== Theoretical significance ==
+The graphism thesis has implications for several areas within the philosophy of science and epistemology. By drawing attention to the material practices through which scientific knowledge is produced and communicated, it supports the broader STS perspective that science should be understood not primarily through abstract logical principles but through the concrete activities of scientists.
+The thesis also relates to discussions of the hard and soft science distinction. Traditional accounts have tended to characterize hard sciences as those that are more mathematical or that achieve greater consensus. The graphism thesis offers an alternative empirical indicator—visual inscription practices—that may capture disciplinary differences more precisely than measures based on mathematization alone.
+Furthermore, the concept of inscriptions as immutable mobiles has been applied beyond the natural sciences to fields including accounting, digital humanities, and cartography, where scholars have examined how visual representations function to stabilize and circulate knowledge claims across institutional and geographical distances.
+
+
+== Criticism and limitations ==
+Latour himself acknowledged a tension within the graphism thesis: while he generally stressed the centrality of visual inscriptions such as graphs, he also wrote at times as if equations—a non-visual form of inscription—were the most immutable and mobile of all inscriptions. How well these remarks cohere with the general emphasis on visual graphism has been noted as an unresolved issue in his work.
+Critics of Latour's inscription framework more broadly have questioned whether treating scientific instruments solely as "inscription devices" adequately captures the role that instruments play in mediating the relationship between scientists and the phenomena they study. Postphenomenological approaches have argued that Latour's semiotic framing of inscriptions overlooks the way instruments actively structure scientists' perceptual and interpretive engagement with reality.
+
+
+== See also ==
+Actor–network theory
+Hard and soft science
+Philosophy of science
+Epistemology
+Visual communication
+Scientometrics
+Data visualization
+Graphism
+
+
+== References ==
+
+
+== Further reading ==
+Best, L. A.; Smith, L. D.; Stubbs, D. A. (2001). "Graph Use in Psychology and Other Sciences". Behavioural Processes. 54 (1–3): 155–165. doi:10.1016/S0376-6357(01)00156-5. PMID 11369467.
+Krohn, R. (1991). "Why Are Graphs So Central in Science?". Biology and Philosophy. 6 (2): 181–203. doi:10.1007/BF02426837.
+Lynch, Michael; Woolgar, Steve (1990). Representation in Scientific Practice. Cambridge, MA: MIT Press. ISBN 978-0-262-62076-5.

data/en.wikipedia.org/wiki/HARKing-0.md

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data/en.wikipedia.org/wiki/Heterophenomenology-0.md

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+---
+title: "Heterophenomenology"
+chunk: 1/1
+source: "https://en.wikipedia.org/wiki/Heterophenomenology"
+category: "reference"
+tags: "science, encyclopedia"
+date_saved: "2026-05-05T03:15:54.411209+00:00"
+instance: "kb-cron"
+---
+
+In the thought of the philosopher Daniel Dennett, heterophenomenology ("phenomenology of another, not oneself") is an explicitly third-person, scientific approach to the study of consciousness and other mental phenomena. It consists of applying the scientific method with an anthropological bent, combining the subject's self-reports with all other available evidence to determine their mental state. The goal is to discover how subjects see the world themselves, without taking the accuracy of the subject's view for granted.
+
+
+== Overview ==
+Heterophenomenology is put forth as the alternative to traditional Cartesian phenomenology, which Dennett calls "lone-wolf autophenomenology" to emphasize the fact that traditional phenomenology accepts the subject's self-reports as being authoritative. In contrast, heterophenomenology considers the subjects authoritative only about how things seem to them. It does not dismiss the Cartesian first-person perspective, but rather brackets it so that it can be intersubjectively verified by empirical means, allowing it to be submitted as scientific evidence.
+The method requires a researcher to listen to the subjects and take what they say seriously, but to also look at everything else available to them, including the subject's bodily responses and environment, evidence provided by relevant neurological or psychological studies, the researcher's memories of their own experiences, and any other scientific data that might help to interpret what the subject has reported.
+Dennett notes this method is actually the normal way that anyone will choose to investigate aspects of the mind. He writes: "heterophenomenology is nothing new; it is nothing other than the method that has been used by psychophysicists, cognitive psychologists, clinical neuropsychologists, and just about everybody who has ever purported to study human consciousness in a serious, scientific way".
+The key role of heterophenomenology in Dennett's philosophy of consciousness is that it defines all that can or needs to be known about the mind. For any phenomenological question "why do I experience X", there is a corresponding heterophenomenological question "why does the subject say 'I experience X'". To quote Dennett, "The total set of details of heterophenomenology, plus all the data we can gather about concurrent events in the brains of subjects and in the surrounding environment, comprise the total data set for a theory of human consciousness. It leaves out no objective phenomena and no subjective phenomena of consciousness."
+
+
+== See also ==
+
+
+== Notes ==
+
+
+== References ==
+Dennett, D. "Heterophenomenology" in Dennett, D. Consciousness Explained, Penguin Press, 1991.
+Dennett, D. (October 2003). "Who's On First? Heterophenomenology Explained" (PDF). Journal of Consciousness Studies. 10 (9–10): 19–30. Archived from the original (PDF) on 2012-02-05.
+Dennett, D. "Heterophenomenology Reconsidered", May 31, 2006.
+Max Velmans, Heterophenomenology vs. critical phenomenology ...https://philpapers.org/rec/VELHVC
+
+
+== External links ==
+ Consciousness studies at Wikibooks