Labor Law Reform and the Role of Delay in Union Organizing: Empirical Evidence from Canada
Bibliographic record
Abstract
This paper examines the determinants and consequences of delay in the union certification process using data from certification applications and unfair labor practice complaints (ULPs) from British Columbia (1986–98) and Ontario (1993–98). During the period studied, there were several changes in delay-related laws, including laws regulating the presence and stringency of election time limits and the availability of expedited ULP hearings. Key findings are that ULPs against the employer reduced the likelihood of compliance with time limit laws except where expedited ULP hearings also existed; employer-filed objections to the application reduced the likelihood of compliance; and election delay reduced the likelihood of certification success both in policy regimes without time limits and in those where stipulated time limits were frequently breached. Overall, the results suggest that enforced time limits on elections coupled with expedited ULP hearings may substantially mitigate the adverse effects of election delay on certification success.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".