Academic Integrity in Work-Integrated Learning (WIL) Settings
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This chapter highlights the imperative for attention to, and action in, the promotion of academic integrity in work-integrated learning (WIL) settings across post-secondary programs. The importance of such efforts are closely tied to the efforts of strengthening ethical comportment with graduates who will go on to contribute to client care, client service, leadership, and research that will directly impact members of the public, hiring organizations, and global systems. WIL settings provide invaluable opportunities for students to learn essential skills and acculturate to professional ethical values through real world experiences. The experiential learning that happens in these settings helps influence the professionalization of students, encouraging safe, ethical practice that benefits those receiving care/service, future employers, and society. Since WIL is offered in both college and university settings and occurs across a number of professional and service programs, it has the potential to significantly influence a vast and varied number of professionals entering numerous career paths around the world. All members of learning communities in post-secondary organizations have a responsibility to understand their roles and opportunities in supporting, maintaining, and promoting academic integrity across WIL settings. While the narrative for the chapter is Canadian, the observations and recommendations may be relevant in other countries, where WIL plays a significant role in the education and development of professionals and service providers across a number of professions and trades.
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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 | 0.017 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.007 | 0.123 |
| Insufficient payload (model declined to judge) | 0.007 | 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 it