Bibliographic record
Abstract
This edited collection is the culmination of a comparative project on 'Voices at Work' funded by the Leverhulme Trust 2010–2013. The book aims to shed light on the problematic concept of worker 'voice' by tracking its complex interactions with various forms of law. Contributors to the volume identify the scope for continuity of legal approaches to voice and the potential for change in a sample of industrialized English speaking common law countries, namely Australia, Canada, New Zealand, UK, and USA. These countries, facing broadly similar regulatory dilemmas, have often sought to borrow and adapt certain legal mechanisms from one another. The variance in the outcomes of any attempts at 'borrowing' seems to demonstrate that, despite apparent membership of a 'common law' family, there are significant differences between industrial systems and constitutional traditions, thereby casting doubt on the notion that there are definitive legal solutions which can be applied through transplantation. Instead, it seems worth studying the diverse possibilities for worker voice offered in divergent contexts, not only through traditional forms of labour law, but also such alternative disciplines.. This book comprises contributions from many leading scholars of labour law, politics, and industrial relations drawn from across the jurisdictions. It is addressed to academics, policy makers, legal practitioners, legislative drafters, trade unions, and interest groups alike. Additionally, while offering a critique of existing laws, this book proposes alternative legal tools to promote engagement with a multitude of 'voices' at 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.067 | 0.022 |
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".