Reflections on Inertia, Movement and Convergence in Out-of-Place Labour Relations: Taking Geography Seriously in Labour Law
Bibliographic record
Abstract
Abstract This essay explores the conceptual and methodological contribution of a spatial understanding of labour law, examining the ways in which labour laws create sites of inclusion and exclusion that can be subverted by worker action. It argues that labour relations cannot be apprehended without considering their place in space. It further argues that labour laws tend to foster inertia within industrial relations by recognizing certain workspaces while failing to adapt to the dynamic geographies of the workplace. Methodologically, this implies a shift from a neutral discourse of rights to one that is anchored in social life where workers converge. This essay suggests that recognizing concrete and dynamic spaces of labour within legislation can lead to upholding diverse voices at work, especially from workers traditionally left in the margins, like women, minorities, and migrants.
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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 | 0.016 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.015 | 0.186 |
| Scholarly communication | 0.024 | 0.022 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".