Collective Representation and Employee Voice in the US Public Sector Workplace: Looking North for Solutions?
Bibliographic record
Abstract
Legislation enacted in many states following the 2010 elections in the United States strengthened unilateral public employer control and weakened employee voice. This rebalancing of power occurred in the context of state public employee labour relations acts modeled on the National Labor Relations Act (NLRA), but with a narrower scope of bargaining than in the private sector. This narrow scope channels unions’ voice away from the quality of public services and towards protecting members from the effects of decisions unilaterally imposed by management. The Supreme Court of Canada has held that the freedom of association guaranteed by the Charter of Rights and Freedoms includes a right to collective bargaining, but that this right need not be modelled on the NLRA. This article explores the evolving Canadian jurisprudence decoupling the right to a voice at work from an NLRA-style model as an alternative approach for US public sector labour law reform.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.040 |
| Scholarly communication | 0.017 | 0.015 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.010 | 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".