Trade Unions, Vocational Education and Workplace Training: International Trends
Bibliographic record
Abstract
Trade unions are struggling to find an appropriate role in the changing world of work and skills requirements. In coordinated market economies (CMEs), where there is a strong tradition of social partnership, shared responsibilities for vocational education and workplace training (VET) have been taken by government, employers, unions and individuals. Yet even in Germany and the Nordic countries, which have a long history of social partnership, there is growing resistance by employers to meet the costs of VET, except where these coincide with their own priorities. In liberal market economies (LMEs), such as the UK and Canada, unions have generally failed to establish long-term partnerships with employers in relation to training, which is generally regarded as a managerial prerogative. Some governments in LMEs have recognized the need for greater investment in VET but have been reluctant to legislate to require employers to fund industry-wide programs of VET and skills development or to ensure that unions are given a legitimate role in these matters.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.014 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".