Migrant Labour, Working Conditions and Complex Jurisdictions in Asian Distant Water Fisheries
Bibliographic record
Abstract
Abstract The global fishing industry is a vital part of the global food system, but it is also a sector in which abuses of migrant workers on fishing vessels have been widely reported. This chapter draws upon global reports from academic, journalistic and advocacy organisations concerning labour conditions in the global fishing industry, as well as our own extensive research interviews with crew members and other key actors in the fishing and migrant deployment industries. We examine the various geographies of labour migration for work on distant water fishing vessels, with a particular focus on the recruitment of Indonesian and Filipino workers on Taiwanese distant water fishing fleets. We also describe the nature of work for migrant crews on board fishing vessels, paying particular attention to reasons why working conditions and power relations have been so problematic in the sector. Finally, we explore the ways in which fishing work is distinctive in terms of how jurisdiction is exercised, creating conditions conducive to labour abuse, especially among migrant crew members; but we also suggest that pressure from consumers, campaigning NGOs and researchers has led governments to start tackling the most egregious cases of abusive working conditions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".