Bibliographic record
Abstract
In recent years, there has been a tendency to view the subject of labour law and its goals through the prism of philosophy, and political philosophy in particular. A veritable ‘cottage industry’ has sprung up devoted to this task. In this paper, I analyze the arguments presented by various authors in a book recently published under the editorship of Professor Brian Langille on The Capability Approach to Labour Law, which makes an important contribution to labour law scholarship. I make the point that the capabilities approach – a theory belonging to political philosophy – is undoubtedly a useful instrument insofar as it enables labour lawyers to sell the claims and arguments that the subject is attempting to make, but that if it is presented as an ostensibly univocal foundation, it is unlikely to stack up. Instead, by abstracting its partial and pluralist base, capabilities can be reconceptualised as only one justification for particular labour laws, serving alongside many other political philosophies. In this way, a veritable patchwork quilt of different foundations for specific labour laws can be stitched together. This paper then goes on to make some preliminary observations as to how such a fabric could be embroidered in a coherent and systematic manner.
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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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.080 |
| Scholarly communication | 0.015 | 0.031 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.007 | 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".