Bibliographic record
Abstract
Media, industry, and other public actors have claimed that a ‘skills gap’ exists in students exiting post-secondary education and entering the workforce. The Ontario provincial government has developed policy, the Highly Skilled Workforce Strategy, to provide directives to universities in the province to provide skills development to students to aid in closing the gap and providing a workplace relevant education. In this study, I explore the experiences of student affairs and services (SAS) staff responsible for enacting provincial policy related to skills development at the university level by investigating the discourses that shape policy and practices of these staff in their daily work. Data collected from documents related to the issue of skills, and from interviews with SAS staff, provided insight into how the problem of skills is represented in policy and in practice. Discourses shaping the practice of SAS staff related to skills development at times conflicted the discourses shaping the issue of skills in policy, but a neoliberal economic rationality is embedded within the broader representation of the issue of skills, with discursive implications for SAS staff and for students.
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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.012 | 0.016 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 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".