Regulating for Decent Work: New Directions in Labour Market Regulation
Bibliographic record
Abstract
Regulating for Decent Work is an international and interdisciplinary response to the neoliberal ideologies that have shaped labour market regulation in recent decades. It draws on contributions by leading experts across a range of disciplines, including economics, law, political science and industrial relations. International in scope, it includes chapters on both advanced economies (Canada, Europe, United States) and the developing world (Brazil, China, Indonesia, Tanzania). The volume identifies central themes in the contemporary regulation of labour, including the role of empirical research in assessing and supporting labour market interventions, the regulation of precarious work and the emergence of new types of labour markets. Each theme is explored through key contributions by leading experts. Chapters cover issues that include labour market uncertainty, the effectiveness of legal norms and methodologies for evaluating the intersection of various levels of regulation. The book advances the academic and policy debates on post-crisis labour regulation by identifying new challenges, subjects and theoretical perspectives. In contrast to the dominant deregulatory approaches, it calls for labour market regulation to be reinvigorated. Co-published with Palgrave Macmillan. Advances in Labour Studies is a wide-ranging series of research titles from the International Labour Office, offering in-depth analysis of labour issues from a global perspective. The series has an interdisciplinary flavour that reflects the unique nature of labour studies, where economics, law, social policy and labour relations combine. Bringing together work from researchers from around the world, the series contributes new and challenging research and ideas that aim both to stimulate debate and inform policy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.037 |
| Scholarly communication | 0.017 | 0.023 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".