What could #metascience learn from #criminology for the prevention of #researchmisconduct and #researchintegrity violations? In a seminar at the Netherlands Institute for the Study of Crime and Law Enforcement (NSCR), I discussed with researchers in criminology how theories and findings from the field may be applied in the field of meta research.
Blog: https://renebekkers.wordpress.com/2025/01/24/how-can-criminology-help-reduce-research-integrity-violations/
Slides: https://renebekkers.wordpress.com/wp-content/uploads/2025/01/how-can-criminology-help-reduce-research-integrity-violations.pptx
[#]peerreview
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Research integrity violations are actions deemed undesirable by the scientific community, codified in guidelines such as the Netherlands Code of Conduct for Research Integrity. Integrity violations are ordered on a continuum of from minor to grave offenses. Fabrication, falsification and plagiarism are commonly viewed as more serious offenses than questionable research practices and ‘sloppy science’.
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Data from the Netherlands Survey of Research Integrity show that the likelihood of detection is low for the most serious offense (data fabrication). Violations of the code of conduct are like crime in the sense that questionable research practices are more prevalent among respondents saying that the likelihood of detection of data fabrication is lower. Data and methods transparency are lower among those saying that the likelihood of detection of data fabrication is lower.
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Research integrity violations are also like crime in the sense that they follows a power law, with a minority of actors responsible for a majority of the violations. Also there is a large dark number of violations of research integrity that are not detected – hence the iceberg metaphor in https://detectingbadscience.wordpress.com/. Criminology itself seems no different from other disciplines in the prevalence of questionable research practices.
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The discussion produced three insights. First, research integrity violations are most similar to other so called victimless crimes such as administrative fraud and tax evasion. Strictly speaking they are not victimless because we are all victims. Fabrication of data in medical research can cause excess deaths of future patients, though at the time of the fraud they are not yet identified.
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Second, legal punishment is based on the premise that perpetrators know the law, and that violations can clearly be identified. However, knowledge of the code of conduct for research integrity is lacking, and awareness of the procedures and potential sanctions for violations of research integrity is low. Also the label ‘questionable research practices’ suggests that in science there is a grey area of practices which are not equivocally wrong.
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For these violations, perpetrators may say they were unaware of the rules of science, and whether they apply in their cases application is doubtful anyway.
Third, research integrity violations are not actively prosecuted. There are some sleuths and data detectives, but we have no police force in science that actively identifies research integrity violations. The peer review process presumes trustworthiness, while mounting evidence suggests that it is not equipped to keep the bad science out.
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With a low chance of being detected and no meaningful sentences, research integrity is mostly a personal responsibility of researchers. Incentives in academia to produce as much output as possible create temptations for researchers to cut corners and engage in bad science. The rapid development of AI tools enabling data fabrication and production of low quality if not erroneous research only makes things worse.
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A large number of questions are left. Where should policing efforts in science be directed? Would it be more efficient to focus on serial offenders of research integrity rather than on occasional offenders? In which circumstances do higher sentences and a higher likelihood of punishment reduce research integrity violations? What are the risks of increasing the punishment and likelihood of detection of violations?
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How should prevention programs be designed to reduce the prevalence of research integrity violations? I’d love to hear your views on these questions!
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@renebekkers
How would you justify any policing or prevention programs? A criminological approach that is convinced from the start that formalized control is necessary, seems problematic to me. Labelling theory would strongly argue against such an approach and even Mertonian sociology of deviance would be an uneasy fit.
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@MartinReinhart perhaps the negative side effects of a control approach are worse than the benefits of compliance - proportionality is key. I was hoping that criminology has produced insights on these side effects
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@renebekkers what if the control approach is the side effect? a foucauldian or cultural theory of crime perspective might ask the question that way, because your "benefits" and "side effects" might not measure on the same scale and, thus, have no proportionality.
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@MartinReinhart thanks - it would be good to know more about applications of these theories from empirical studies
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@renebekkers i offered four theoretical perspectives that were all built by knowledgeable academic communities by reflecting on 150+ years of empirical criminological research and the field has even more than just those four. consideration of the strategic theoretical relevance of future studies is key.
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@MartinReinhart Thank you for these pointers. I'm new to the field and eager to learn. It will be good to take the insights from these theories into account when thinking about quality control and governance instruments in science
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@renebekkers self plug on these issues:
https://doi.org/10.1080/23299460.2024.2414491
https://doi.org/10.1177/0306312720975201
https://doi.org/10.1177/0011392116663807
http://www.forschungsinfo.de/Publikationen/Download/publications-02-00061-1.pdf
https://www.rmz.hu-berlin.de/en/research/publishing
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@MartinReinhart wow - thanks!
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@MartinReinhart very useful and interesting work! Link #3 produces this
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@renebekkers works on my side. maybe the direct link works: https://journals.sagepub.com/doi/10.1177/0011392116663807
preprints are linked here: https://hu.berlin/reinhart
and as always: happy to send things via email.
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@MartinReinhart this link works, thanks
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