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Record W2982586741 · doi:10.1136/bmj.l6320

Research integrity: UK guidelines are updated to ensure misconduct reporting

2019· article· en· W2982586741 on OpenAlexaboutno aff
Elisabeth Mahase

Bibliographic record

VenueBMJ · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicAcademic integrity and plagiarism
Canadian institutionsnot available
Fundersnot available
KeywordsResearch integrityScientific misconductMisconductTransparency (behavior)Scientific integritySanctionsQuarter (Canadian coin)Political scienceHouse of CommonsAcademic integrityPublic relationsEngineering ethicsEngineeringMedicineLaw

Abstract

fetched live from OpenAlex

The national guidelines on research integrity have been updated to clarify the requirements for universities and enable sanctions to be enforced when research misconduct takes place.1 The move follows a July 2018 report by the House of Commons Science and Technology Select Committee, which found that a quarter of UK universities failed to produce an annual report on research integrity.2 The committee said that the “lack of consistent transparency” in reporting data on the number of misconduct investigations, …

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.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearchResearch integrity
Domain: Evaluation · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptMetaresearchResearch integrity
Domain: Methods · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.024
metaresearch head score (Gemma)0.029
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.277
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.002

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 head0.303
GPT teacher head0.511
Teacher spread0.207 · 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

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

Study designNot applicable
DomainEvaluation · Methods
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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Same venueBMJSame topicAcademic integrity and plagiarismCategoryMetaresearchFrench-language works237,207