Academic Integrity in Selected Western Canadian Colleges and Polytechnics: A Policy Analysis
Bibliographic record
Abstract
Canadian colleges and polytechnics have been neglected in research on academic integrity, with some exceptions. Therefore, we examined academic integrity policy documents (N = 36) from 16 publicly-funded colleges and polytechnics in Alberta and Manitoba, Canada, replicating a qualitative research design used in previous research. Data were analyzed through the lens of five core elements of exemplary academic integrity policy. Access to policy was straightforward using the search engine present on institutional websites. In terms of approach, the three most frequently identified principles were natural justice/procedural fairness/timeliness, punitive, and ethics/integrity values/standards. The student was identified as the locus of responsibility for upholding academic integrity as a matter of student conduct, with faculty and administrators responsible for investigating and addressing misconduct after cases come to light. Within the documents, detail was extensive with plagiarism, cheating, breaches of exam integrity, collusion, falsification, fabrication, and intentional misrepresentation describing misconduct most commonly. Most documents described supports in the form of procedural steps for reporting academic misconduct, with minimal mention of proactive or remedial education. We also examined whether equity, diversity, inclusion, accessibility, decolonization, and Indigenization (EDIA-DI) were considered within these documents and found little attention was paid to these values. We call for colleges and polytechnics to update approaches to policy design that include a focus on EDIA-DI, connect academic integrity and professional ethics to educate students on institutional expectations and conduct more research to inform the development of strategies that nurture cultures of academic 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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".