FOR THE CHALLENGE TO UNIONS TO ORGANISE
Bibliographic record
Abstract
Post published a series of articles gloating over the travails of the Canadian labour movement (Brieger 2003; Corcoran 2003; Milhar 2003a and b). The articles reported on a poll commissioned by the notoriously anti-union Union Watch but conducted by Leger Marketing. The Post claimed, among many other things disturbing to unions, that organised labour’s share of Canadian workers had dropped dramatically from the 1970s, that a large majority of non-union employees did not want a union and that only about of union members are “very satisfied ” with their union’s representation of their interests. Many of the poll questions and much of the Post’s analysis were driven by antipathy to unions, it is true. The poll results do not always support the conclusions that the Post draws. It is also interesting to note that among union members polled, 81 % want to stay in their unions (the exact same proportion of non-unionists who reject unions). An earlier poll by Americans Richard Freeman and Joel Rogers (1999) calls some of the Canadian results into question. In their American poll, the authors found 32 % of non-union employees would choose a union. Does this make Canadians more anti-union than Americans? More importantly, Freeman and Rogers found a powerful desire among workers for representation of their interests in the workplace. Over half of the workers polled wanted more influence in their workplace than they actually had.1 Whether such influence could be achieved through unions or not is a challenge to unions.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.014 |
| Scholarly communication | 0.019 | 0.013 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.020 | 0.021 |
| Insufficient payload (model declined to judge) | 0.057 | 0.020 |
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".