Evidence map›Paper›PMID 28281156›Full record

ArticleScience and engineering ethics2018

Questionable, Objectionable or Criminal? Public Opinion on Data Fraud and Selective Reporting in Science.

Justin T Pickett, Sean Patrick Roche

Abstract read
PubMed Publisher
In one paragraph

Article in Science and engineering ethics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Image fraud in nuclear medicine research.European journal of nuclear medicine and molecular imaging · 2026
    Article
  6. Review
  7. Reproducibility in the Social Sciences.Annual review of sociology · 2022
    Article
  8. Article
  9. Review
  10. Article
  11. Criminalization of scientific misconduct.Medicine, health care, and philosophy · 2019
    Article
  12. Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Justin T PickettSchool of Criminal Justice, University at Albany - State University of New York, 135 Western Avenue, Albany, NY, 12222, USA. jpickett@albany.edu.
Sean Patrick RocheSchool of Criminal Justice, University at Albany - State University of New York, 135 Western Avenue, Albany, NY, 12222, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Data fraud and selective reporting both present serious threats to the credibility of science. However, there remains considerable disagreement among scientists about how best to sanction data fraud, and about the ethicality of selective reporting. The public is arguably the largest stakeholder in the reproducibility of science; research is primarily paid for with public funds, and flawed science threatens the public's welfare. Members of the public are able to make meaningful judgments about the morality of different behaviors using moral intuitions. Legal scholars emphasize that to maintain legitimacy, social control policies must be developed with some consideration given to the public's moral intuitions. Although there is a large literature on popular attitudes toward science, there is no existing evidence about public opinion on data fraud or selective reporting. We conducted two studies-a survey experiment with a nationwide convenience sample (N = 821), and a follow-up survey with a representative sample of US adults (N = 964)-to explore community members' judgments about the morality of data fraud and selective reporting in science. The findings show that community members make a moral distinction between data fraud and selective reporting, but overwhelmingly judge both behaviors to be immoral and deserving of punishment. Community members believe that scientists who commit data fraud or selective reporting should be fired and banned from receiving funding. For data fraud, most Americans support criminal penalties. Results from an ordered logistic regression analysis reveal few demographic and no significant partisan differences in punitiveness toward data fraud.

Indexed as

AttitudePublic OpinionSocial Control, FormalBiomedical ResearchCriminalsEthics, ResearchFraudHumansMoralsResearch DesignResearch PersonnelScientific MisconductSurveys and QuestionnairesFabrication and falsificationFalse positivesPublication biasQuestionable research practicesResearcher degrees of freedomResearch misconduct

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.