Hire Education: Work Integrated Learning and Sense of Belonging for International Students
Bibliographic record
Abstract
International students in Canadian institutions of higher education face multiple barriers to experiencing a full sense of belonging. While these barriers impact their ability to engage fully with their academic programs, they also affect opportunities for post-graduation employment. Work integrated learning has many pre- and post-graduation benefits for students, including increased opportunities for employment. In this dissertation-in-practice, the problem of practice presented explores sense of belonging through the role work integrated learning plays in international students securing post-graduation employment. It proposes an alternate program stream for international students that provides access to work integrated learning opportunities. This stream embeds targeted supports for international students and their placement employers. This proposed program stream embodies the ethics of care and community as grounding principles. Consideration for the problem of practice is through a leadership approach rooted in transformational and distributed leadership and critical reflection. I deliberately address the limitations of my middle manager role through a collaborative agency approach. Guided by activity theory, an examination of the organizational context at Career Ready College (a pseudonym) identifies implementation opportunities and barriers to the proposed change. Sense of community theory grounds the conceptual framework, and the change planning incorporates the change path model. Also included is a plan for monitoring, evaluating, and communicating the proposed change. The dissertation-in-practice concludes with recommendations for expanded work integrated learning opportunities for international students in additional programs at Career Ready College and beyond.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".