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Record W4291201867 · doi:10.1177/00113921221117604

Sentencing social psychology: Scientific deviance and the diffusion of statistical rules

2022· article· en· W4291201867 on OpenAlex
Julien Larrègue

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCurrent Sociology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Deviance, and Social Control
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsDeviance (statistics)AppealSanctionsScientific misconductMisconductSociologyCriminologyField (mathematics)PsychologySocial psychologyLawPolitical science

Abstract

fetched live from OpenAlex

This article investigates the inquiries and sanctions that followed accusations of fraud directed toward Dutch social psychologist Diederik Stapel in the early 2010s. Relying on the public reports published by the investigative committees, as well as on interviews conducted with committee members and Stapel’s former students and collaborators, we propose to analyze how this case facilitated the diffusion, in social psychology, of statistical rules that were hitherto unenforced in this field. The Stapel case thus illustrates the regulative role played by statistics in the contemporary scientific field while also demonstrating the appeal of legal modes of dealing with misconduct when it comes to the treatment of scientific deviance. More generally, this article shows how the study of scientific deviance can serve to bring to light symbolic hierarchies that are habitually kept tacit, thus serving as a magnifying glass for the scientific field’s inner processes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.007
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.053
GPT teacher head0.397
Teacher spread0.344 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it