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Record W2958383422 · doi:10.11575/prism/36484

Building a regional academic integrity network: Profiling the growth and action of the Academic Integrity Council of Ontario

2019· article· en· W2958383422 on OpenAlexaboutno aff
Andrea Ridgley, Jennifer Miron, Amanda McKenzie

Bibliographic record

VenueOpen MIND · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Education and Practice Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsAcademic integrityResearch integrityData integrityProfiling (computer programming)Political scienceComputer securityEngineering ethicsPublic relationsComputer scienceEngineering

Abstract

fetched live from OpenAlex

Since 2009, the Academic Integrity Council of Ontario (AICO) has provided a forum for practitioners and representatives from post-secondary institutions in Ontario to share information, and to facilitate the establishment and promotion of academic integrity best practices in Ontario colleges and universities. This presentation by members of AICO describes the role of the council and how it serves to connect post-secondary institutions in Ontario on academic integrity-related matters. We’ll discuss the benefits that such association between institutions brings, how collaboration and group problem-solving is encouraged and the accomplishments that working together have brought to date, such as the establishment of a sub-committee to examine contract cheating. Join us to learn about our experiences and lessons learned and to gain information on how to collaborate with like-minded colleagues, gain support, and produce cross-institutional resources. Workshop presented at the Canadian Symposium on Academic Integrity, held at the University of Calgary, April 17-18, 2019

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.865
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.281
GPT teacher head0.433
Teacher spread0.152 · 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 designNot applicable
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

Citations2
Published2019
Admission routes1
Has abstractyes

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