Advancements in Work-Integrated Learning Research: Editorial Insights
Bibliographic record
Abstract
Over the past two decades, scholarship into work-integrated learning (WIL) has significantly expanded, highlighting the importance of its contribution to higher education. The International Journal of Work-Integrated Learning (IJWIL) has been an important part of the promotion of research and scholarship of WIL, and the dissemination of new knowledge. This current IJWIL Issue includes three articles that provide a bibliometric analysis of what is now a significant body of WIL literature. These analyses reveal trends in themes such as equity and access, professional identity development, stakeholder engagement, risks, and highlight the high level of collaboration among WIL researchers. This editorial emphasizes the advances of WIL scholarship by further identifying key developments and topical challenges and linking these to recent published WIL literature to inspire further research to enhance the understanding of WIL as a transformative pedagogy.
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 | 0.025 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.018 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".