The Legal Production of Precarious Work
Bibliographic record
Abstract
Globalisation, the shift from manufacturing to services as a source of employment, and the spread of information-based systems and technologies have given birth to a new economy, which emphasises flexibility in the labour market and in employment relations. These changes have led to the erosion of the standard (industrial) employment relationship and an increase in precarious work - work which is poorly paid and insecure. Women perform a disproportionate amount of precarious work. This collection of original essays by leading scholars on labour law and women's work explores the relationship between precarious work and gender, and evaluates the extent to which the growth and spread of precarious work challenges traditional norms of labour law and conventional forms of legal regulation. The book provides a comparative perspective by furnishing case studies from Australia, Canada, the Netherlands, Quebec, Sweden, the UK, and the US, as well as the international and supranational context through essays that focus on the IMF, the ILO, and the EU. Common themes and concepts thread throughout the essays, which grapple with the legal and public policy challenges posed by women's precarious work.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.056 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".