Beyond Employability: Defamiliarizing Work-Integrated Learning with Community-Engaged Learning
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
Within the context of an increasing interest in forms of work-integrated learning (WIL) among governments and institutions of higher education, this essay explores the relation between WIL and community-engaged learning (CEL) in order to argue that the structural and self-critique apparent in much CEL scholarship can serve as a model to WIL scholars and practitioners. CEL has undergone a rigorous process of self-examination in recent years, a process that has encouraged its advocates to think carefully about their core assumptions, appropriate learning objectives, and best practices in the field. In this way, we argue, whether or not CEL is classified as a form of WIL, it can serve to defamiliarize many of WIL’s assumptions and to invite self-reflection in the field as a whole. In the first half of the essay, we provide background for the conversation, first in the Canadian context, and then in the broader scholarship of CEL. In the second half, we offer three case studies that illustrate both the distinctive characteristics of CEL and, in the last case, how these characteristics might strengthen the practice of traditional WIL.
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.
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 | 0.888 | 0.855 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.774 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.892 |
| Insufficient payload (model declined to judge) | 0.000 | 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