Plagiarism: A Canadian Higher Education Case Study of Policy and Practice Gaps
Bibliographic record
Abstract
This mixed methods case study investigated faculty perspectives and practice around plagiarism in a Western Canadian faculty of education. Data sources included interviews, focus groups, and a survey. Findings showed that participants (N = 36) were disinclined to follow established procedures. Instead, they tended to deal with plagiarism in informal ways without reporting cases to administration, which resulted in a disconnect between policy and practice. The emotional impact of reporting plagiarism included frustration with the time required to document a case, and fear that reporting could have a negative effect on one’s employment. Recommendations include approaches that bridge the gap between policy and practice. Key words: Academic integrity, plagiarism, Canada, higher education, faculty Cette étude de cas à méthodes mixtes s’est penchée sur les perspectives et les pratiques du corps professoral relatives au plagiat dans une faculté d’éducation dans l’ouest du Canada. Les sources de données ont inclus les entrevues, les groupes de discussion et un sondage. Les résultats indiquent que les participants (N=36) étaient peu portés à suivre les procédures établies. Ils avaient plutôt tendance à employer des moyens informels pour traiter le plagiat, sans signaler les cas à l’administration, ce qui entrainait un écart entre la politique et la pratique. L’impact émotionnel découlant du signalement du plagiat comprenait le temps nécessaire à documenter un cas et la peur que le signalement puisse avoir une incidence négative sur son emploi. Les recommandations proposées incluent des approches visant à combler l’écart entre la politique et la pratique. Mots clés : intégrité académique, plagiat, Canada, enseignement supérieur, faculté
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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 arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Research integrity Domain: not available · Genre: Empirical About the Canadian research system: yes · About a Canadian topic: yes | Qualitative | low |
| gpt | MetaresearchResearch integrity Domain: Methods · Genre: Empirical About the Canadian research system: yes · About a Canadian topic: yes | Qualitative | high |
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 | 0.003 | 0.069 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".