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Record W2342525931 · doi:10.47678/cjhe.v46i1.185166

Early Contributions to the Evolution of the Canadian Scientific Integrity System: Institutional and Governmental Interaction in the Policy Diffusion Process

2016· article· en· W2342525931 on OpenAlexaffvenueabout
Jordan Richard Schoenherr, Bryn Williams–Jones

Bibliographic record

VenueCanadian Journal of Higher Education · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicAcademic integrity and plagiarism
Canadian institutionsUniversité de MontréalCarleton UniversityUniversity of Ottawa
Fundersnot available
KeywordsResearch integrityMisconductScientific misconductGovernment (linguistics)Consistency (knowledge bases)Process (computing)Political scienceRigourPublic administrationPublic relationsBusinessLaw

Abstract

fetched live from OpenAlex

Academic institutions and research funders have in the last decade devoted considerable effort to developing policies to support academic integrity and prevent misconduct. In this study, we consider the extent to which various initiatives of Canadian federal and provincial (Québec) funders have affected the development of institutional research integrity/misconduct (RIM) policies. Examining the creation and modification dates of 32 institutional RIM policies, we find that federal but not provincial initiatives appear to have the greatest impact on the development of RIM policies. Idiosyncrasies in the creation dates, as well as lack of evidence of a systematic pattern in modification dates, suggest a complex system that is often insulated from certain government initiatives. These results lead us to conclude that there should be greater consistency in the development or updating of RIM policies to ensure the appropriate treatment of misconduct and to encourage behaviour that meets the highest standards of research integrity.

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

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.786
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.310
Teacher spread0.298 · 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

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations5
Published2016
Admission routes3
Has abstractyes

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