The Constitutionalization of Employment Relations: Multiple Models, Pernicious Problems
Bibliographic record
Abstract
The constitutionalization of employment relations has been proposed as a possible response to the serious difficulties confronting workers and unions in an era of neo-liberalism and globalization. This article challenges this proposal on two grounds. First, ‘employment’ no longer serves as an appropriate platform for labour policy, and in any event is conceptually inappropriate for constitutionalization. And second, a survey of the multiple meanings and manifestations of ‘constitutionalization’ at the level of the nation state, the global economy and the enterprise reveals that this approach is unlikely to produce positive practical results for workers. Nonetheless, to think about the constitutionalization of employment relations is productive in the sense that it requires engagement with the pernicious problems of articulating a ‘new normal’ — a ‘new normativity’ — that represents a better balance between workers’ interests and those of employers.
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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 | 0.044 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.099 |
| Scholarly communication | 0.023 | 0.034 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.009 | 0.017 |
| Insufficient payload (model declined to judge) | 0.004 | 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".