Bibliographic record
Abstract
International students are critical to the academic, social and economic vitality of post-secondary institutions in Canada, yet, their retention can be challenging. When relations between host and home nations are strained, students are at risk of being required to return home, or of having their scholarships revoked. During the pandemic, international students, forced to study entirely online due to campus closures, were at risk of not having their visas renewed. Another challenge to international student retention is non-compliance with academic integrity policy. Non-compliance can result in penalties leading to dropouts and expulsion. Unlike other external challenges, ensuring compliance with academic integrity policy is entirely within institutional jurisdiction, yet Canadian colleges and universities assume varying degrees of responsibility in this regard. Using colleges in Ontario, Canada, as a case study, this paper explores the extent to which each of Ontario's 22 English-medium colleges provides its international students with ready access to intelligible academic integrity policy and pro-active training therewith. Using a mixed-methods approach, this research consists of content and document analysis, as well as descriptive statistics, to examine the academic integrity policy and support provisions (accessed online through Google searches) of each college. Colleges were ranked as exemplary, adequate or in need of improvement along a number of dimensions including acknowledging different cultural understandings and availability of translated material. Findings demonstrate that there is much more that colleges can do to support international students (upon whose tuition fees they are so dependent) in the area of understanding academic integrity compliance.
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 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 | 0.020 | 0.088 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.017 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".