Making Union Membership the Default Option in Canada: Would It Be Supported and Effective?
Bibliographic record
Abstract
Income inequality has risen in Canada with the decline in union density and, thus, in union influence. Both trends have occasioned various proposals to reform federal and provincial labour relations systems, especially those aspects concerning certification. However, most proposals have been based on minor modifications to the Wagner Model of exclusive, majoritarian representation. To realize the full potential of these reform proposals, including, importantly, the likes of ‘broad-based bargaining,’ we contend that union membership should be the default option for new workers. Such a change would enable these proposals to increase absolute and relative levels of union membership, thereby providing the organizing resources (financial, human) required for much higher levels of union influence. In this study, we show that those living in Canada generally support union membership by default and would not opt out afterwards. We believe this popular support justifies making union membership automatic for new workers. Abstract Union density has declined in Canada and, with it, wage inequality has risen, occasioning various proposals to reform the certification systems operating provincially and federally. However, such proposals are ordinarily based on only minor changes to the Wagner Model. We contend that to realize the full potential of these proposals, union membership by default is required to increase union membership levels. In this study, we show that those living in Canada generally support union membership as the default option and would not opt out afterwards. We believe this popular support justifies more comprehensive study of the proposal to make union membership automatic for new workers.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.007 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".