"Get them young and train them right": Negotiations in a VET partnership
Bibliographic record
Abstract
This paper explores a high school apprenticeship program in Alberta, Canada, as an example of a market approach to vocational education and training (VET) through social partnership. While this program is seen as a win-win for students and employers, interviews with different partners suggest that there are continuing negotiations over who is responsible for training, who has access to formal training, who pays for it, what kind of knowledge is seen as necessary, how training is delivered, and how it is rewarded by employers. Power relations among the partners are indicated by the outcomes of negotiations and the lack of negotiation in certain areas relevant to effective training. Further, the lack of government incentives for partnership work appears to make programs that involve college training, however beneficial for students, difficult to sustain even in booming economic times. Résumé Cet article étudie un programme d’apprenti ayant cours en Alberta, Canada, qui se veut une façon de faire de l’insertion professionnelle et des stages en milieu de travail impliquant un partenariat social. Même si ce programme est perçu comme une situation gagnant-gagnant par l’employeur et l’étudiant, des entrevues avec différents partenaires laissent croire qu’il y a constamment des négociations à faire afin de savoir qui est responsable de la formation, qui a accès à la formation formelle, qui paie pour la formation, quelles connaissances sont considérées comme nécessaires, quel est le format de la formation et comment elle est reconnue par l’employeur. Des relations de pouvoir entre les partenaires transparaissent de la négociation et du manque de négociation dans certains domaines liés aux programmes de formation. En outre, le manque d’incitatifs gouvernementaux visant à développer le travail coopératif rend difficile la mise en place de programmes associés à une formation collégiale dans un contexte de prospérité économique, même s’ils sont bénéfiques pour les étudiants.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.035 | 0.018 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".