---
title: "Research transparency"
chunk: 3/6
source: "https://en.wikipedia.org/wiki/Research_transparency"
category: "reference"
tags: "science, encyclopedia"
date_saved: "2026-05-05T03:17:09.728209+00:00"
instance: "kb-cron"
---

=== 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 institutions and communities. Between 1979 and 1981, several major cases of scientific frauds and plagiarism draw a larger focus to the issue from researchers and policy-makers in the United States In a well-publicized investigation, Betrayers of Science, two scientific journalists described scientific fraud as a structural problem: "As more cases of frauds broke into public view (…) we wondered if fraud wasn't a quite regular minor feature of the scientific landscape (…) Logic, replication, peer review — all had been successfully defied by scientific forgers, often for extended periods of time". The codification of research integrity has been the main institutional answer to this increased public scrutiny with "numerous codes of conduct field specific, national, and international alike."

=== The reproducibility/transparency debate (2000–2015) ===

In the 2000s, long-standing issues on the standardization of research methodology have been increasingly presented as a structural crisis which "if not addressed the general public will inevitably lose its trust in science." The early 2010s is commonly considered to be a turning point: "it wasn't until sometime around 2011–2012 that the scientific community's consciousness was bombarded with irreproducibility warnings".
An early significant contribution to the debate has been the controversial and influential claim of John Ioannidis from 2005: "most published research findings are false. The main argument was based on the excessively lax experimental standards in place, with numerous weak result being presented as solid research: "the majority of modern biomedical research is operating in areas with very low pre- and post-study probability for true findings"
Due to being published in PLOS Medicine the study of Ioannidis had a considerable echo in psychology, medicine and biology. In the following decades, large range projects attempted to assess experimental reproducibility. In 2015, the Reproducibility Project: Psychology attempted to reproduced 100 studies from three top psychology journals (Journal of Personality and Social Psychology, Journal of Experimental Psychology: Learning, Memory, and Cognition, and Psychological Science): while nearly all paper had reproducible effects, it was found that only 36% of the replications were significant enough (p value above the common threshold of 0.05). In 2021, another Reproducibility Project, Cancer Biology, analyzed 53 top papers about cancer published between 2010 and 2012 and established that the effect sizes were 85% smaller on average than the original findings .
During the 2010s, the concept of reproducibility crisis has been expanded to a wider array of disciplines. The share of citations per year of the seminal paper of John Ioannidis, Why Most Published Research Findings Are False in the main fields of research according to the metadata recorded by the academic search engine Semantic Scholar (6,349 citations as of June 2022) shows how this framing has especially expanded to computing sciences. In Economics, a replication of 18 experimental studies in two major journals, found a failure rate comparable to psychology or medicine (39%).

Several global surveys have reported a growing uneasiness of scientific communities over reproducibility and other issues of research transparency. In 2016, Nature highlighted that "more than 70% of researchers have tried and failed to reproduce another scientist's experiments, and more than half have failed to reproduce their own experiments" The survey also found "no consensus on what reproducibility is or should be", in part due to disciplinary differences, which makes it harder to assess what could be the necessary steps to overcome the issue at plays. The Nature survey has also been criticized for its paradoxical lack of research transparency, since it was not based on a representative sample but an online survey: it has "relied on convenience samples and other methodological choices that limit the conclusions that can be made about attitudes among the larger scientific community" Despite mixed results, the Nature survey has been largely disseminated and ahs become a common entry data for any study of research transparency.
Reproducibility crisis and other issues of research transparency have become a public topic addressed in the general press: "Reproducibility conversations are also unique compared to other methodological conversations because they have received sustained attention in both the scientific literature and the popular press".