Bibliographic record
Abstract
When it comes to analysing exploitative and unfree labour, most research refers to “othering” or “race”. Race is often treated as a given category rather than a social phenomenon that needs explanation. In this article, I draw attention to the question of how racism is preserved, reproduced and changed within and through unfree labour relations. I do this by discussing the conceptual interlinkages between unfree labour, migration and racism. While the role of migration policies should not be underestimated, this should be accompanied by an analytical account of their racist background and outcomes. Based on this I present a framework for the analysis of racism as it relates to unfree labour and migration. I draw attention to three different levels of analysis (historico-structural, discursive-symbolic and everyday practices) and the interrelations between them. For empirical illustrations, I draw on my research on modern slave labour in two production sectors in Brazil: charcoal and clothing. I discuss the empirical findings with regard to three analytical problems in the analysis of unfree labour and racism: the impact of generalising knowledge on (future) migrant workers; the role and responsibility of global production networks; and the need to critically reflect on initiatives and policies aimed at the eradication of unfree labour. KEYWORDS: labour migration; unfree labour; racism; Brazil; workers’ rights
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".