Bibliographic record
Abstract
In recent years job training programs have suffered severe funding cuts and the focus of training programs has shifted to meet the directives of funders rather than the needs of the community. How do these changes to job training affect disadvantaged workers and the unemployed? In an insightful and comprehensive discussion of job education in Canada, Cohen and her contributors pool findings from a five-year collaborative study of training programs. Good training programs, they argue, are essential in providing people who are chronically disadvantaged in the workplace with tools to acquire more secure, better-paying jobs. In the ongoing shift toward a neo-liberal economic model, government policies have engendered a growing reliance on private and market-based training schemes. These new training policies have undermined equity. In an attempt to redress social inequities in the workplace, the authors examine various kinds of training programs and recommend specific policy initiatives to improve access to these programs. This book will be of interest to policymakers, academics, and students interested in policy, work, equity, gender and education.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".