The Effect of Compulsory Certification Votes on Certification Applications in Ontario: An Empirical Analysis
Bibliographic record
Abstract
Labour legislation was amended to require that a union applying to certify a group of employees must obtain at least 50% of the ballots in a mandatory representation vote. These amendments eliminated the card-based certification system that had prevailed until this time, under which a representation vote was required only in cases where the union failed to show membership evidence from 55% of employees in the proposed unit. In this paper, the author presents the results of a statistical analysis which she conducted with respect to the impact of mandatory vote on the certification process, with particular emphasis on the characteristics of bargaining units. Using data obtained from the Labour Relations Board and the province's Ministry of Labour, the study examines certification applications between 1993 and 1998. The author concludes that the overall proportion of successful certification applications is substantially lower under the mandatory vote than it had been under the card-check system. Furthermore, the results show a significant difference in the characteristics of bargaining units, indicating a shift towards larger bargaining units concentrated to a greater degree in the manufacturing sector, and a concurrent decline in certification activity in the service sector and among part-time employees. This, in the author's view, suggests that the mandatory vote has had a disparately negative impact on more vulnerable employees.
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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 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".