Increasing skilled trades employer participation in apprenticeship training in British Columbia
Bibliographic record
Abstract
The sustainability of British Columbia’s economy depends on maintaining a highly-skilled and productive trades labour-force. Since the late-1990s, reports of labour shortages in the trades have become increasingly frequent. Apprenticeship has traditionally been the source of training for new entrants to the trades, yet its contribution to the skilled trades labour force has been in decline in recent decades. In the early 2000s, policy responses targeted increasing the supply of potential apprentices, and produced record high apprenticeship enrolments. However, a decade later, these enrolments have not resulted in additional apprenticeship completions. Only an estimated twenty per cent of skilled trades firms are currently training apprentices. This study examines the factors that affect a firm’s decision whether to participate in apprenticeship by focusing on one sector – the electrical trades in Vancouver, BC. This study’s methodology has two components: a survey of the population of electrical trades firms, and semi-structured interviews with ten firms including four firms that currently employ apprentices, and six firms that currently do not employ apprentices. The study finds that apprenticeship training occurs primarily in larger firms and unionized firms, and participation is primarily dependent on the availability of steady work contracts. Economic volatility, 'underground' competition, and information problems are interrelated factors that present challenges related to economies of scale, which adversely affect the participation of small firms in apprenticeship. Interviews with firms reveal that the current policy framework of directly subsidizing apprenticeship has had no effect on their hiring decisions. To improve the flow of workers into the skilled trades and address apprenticeship barriers, policies will need to focus on producing additional work opportunities that are conducive to apprenticeship training, improving the flexibility of apprenticeship work arrangements, correcting information problems regarding skill assessment, and suppressing 'underground' firms. Policy alternatives include apprentice-share arrangements similar to that of the Canadian Electrical Joint Training Committee (EJTC) or Australian Group Training Organizations (GTOs), and/or an interactive user-supported web platform that provides accurate industry and firm-specific information to other firms, workers, prospective workers, and consumers.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".