Strengthening the research agenda of educational integrity in Canada: a review of the research literature and call to action
Bibliographic record
Abstract
Abstract We present findings of a literature review on the topic of educational integrity in the Canadian context. Our search revealed 56 sources, published between 1992 and 2017. A historical overview showed a rise in the number of scholarly publications in recent years, but with an overall limited number of research contributions. We identified three major themes in the literature: (a) empirical research; (b) prevention and professional development; and (c) other (scholarly essay). Our analysis showed little evidence of sustained research programs in Canada over time or national funding to support integrity-related inquiry. We also found that graduate students who completed their theses on topics related to educational integrity often have not published further work in the field later in their careers. We provide five concrete recommendations to elevate and accelerate the research agenda on educational integrity in Canada on a national level. We conclude with a call to action for increased research to better understand the particular characteristics of educational integrity in Canada.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.050 | 0.133 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.028 | 0.048 |
| Science and technology studies | 0.022 | 0.020 |
| Scholarly communication | 0.027 | 0.010 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".