Work-Integrated Learning Policy in Alberta: A Post-Structural Analysis
Bibliographic record
Abstract
In late 2020 the Government of Alberta’s Ministry of Advanced Education sent a guidance document to Alberta post-secondary institutions to lay out how work-integrated learning was to be conducted. This document also informed the institutions that work-integrated learning should be included in all future program proposals. The guidelines were sent without the context or purpose stated. This paper applies Carol Bacchi’s “What’s the Problem Represented to be” post-structural policy discourse analysis to the Ministry of Advanced Education guidelines. There is a broad consensus in work-integrated learning research that work-integrated learning is beneficial for participants beyond employment outcomes. However, this analysis shows the Ministry of Advanced Education’s representation of the problem displays an assumption that the purpose of work-integrated learning is to improve labour market outcomes. The analysis also spotlights that the likely effects of the policy have more to do with making work-integrated learning programs easier to assess than to improve student education. This paper proposes an alternative framework that would integrate the constructivist and humanistic origin of work-integrated learning and allow institutions to develop appropriate experiential learning components for their programs while still standardizing work-integrated learning components across and within institutions. This proposed framework can improve work-integrated learning programs in Canada by widening the focus beyond human capital theory.
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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 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".