Frustrated Demand for Unionisation: the Case of the United States and Canada Revisited
Bibliographic record
Abstract
In this paper we demonstrate that there is a substantial union representation gap in the United States. We arrive at this conclusion by comparing Canadian and American worker responses to questions relating to desired union representation. We find that a majority of the gap in union density between Canada and the US is a function of greater frustrated demand on the part of American workers. We then estimate potential union density rates for the United States and Canada and find that, given current levels of union membership in both countries, if effective demand for unionisation among non-union workers were realised, then this would imply equivalently higher rates of unionisation (37 and 36 percent in the US and Canada respectively). These results cast some doubt on the view that even minor reforms to labour legislation in the US, to bring them in line with those in most Canadian jurisdictions, would do nothing to improve the rate of organising success in the United States. The results also have implications for countries such as Britain who have recently moved closer to a Wagner-Act model of statutory recognition.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.027 | 0.012 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.017 | 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".