(Re)Conceptualising Unfree Labour: Local Labour Control Regimes and Constraints on Workers' Freedoms
Bibliographic record
Abstract
Disputes over the meaning of human trafficking, forced labour and modern slavery have both provoked and coincided with a reinvigorated debate in academic and policy literatures about how to conceptualise unfree labour. This article traces the contours of the debate over free and unfree labour, identifying its key stakes as the debate has developed and paying particular attention to recent interventions. It begins by identifying a problem common to both canonical liberal and Marxian approaches to the free/unfree labour distinction, which is to fetishise the labour market. It then discusses the consensus that is emerging across disciplines and in leading international organisations that labour unfreedom in contemporary capitalism is best conceptualised as a continuum rather than a binary, highlighting recent disciplinary-specific contributions. It argues that the metaphor of a continuum of labour unfreedom obscures more than it illuminates. Drawing upon the growing body of literature that advocates a multifaceted approach to labour unfreedom, this article argues that a robust concept of local labour control regime does a much better job of capturing the complex mix of consent and coercion involved in extracting value from labour power than the idea of a continuum of labour unfreedom. KEY WORDS: unfree labour; migration; capitalism; exploitation; labour control
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.073 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| 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".