Technologies of Transparency: The Role of Information and Communications Technologies in Promoting Labour Rights in Distant Water Fisheries
Bibliographic record
Abstract
Ethical production networks and supply chains have garnered significant attention in both academia and industry. The ethical supply chain has become a topic of significant debate in the global fishing industry in particular, and especially in distant water fishing (DWF). Monitoring labour rights/abuses presents a challenge in this field, as workers are employed on fishing vessels operating in isolated and remote waters, often outside any effective oversight or regulation. This study aims to investigate the potential of various information and communication technologies (ICTs) in tracking, monitoring, and promoting labour rights in DWF. In pursuing this question, I use the intersection of global production networks (GPN) and labour regimes as a theoretical framework. While GPN theory addresses the institutions, actors and power relations in global production processes, labour regime theory provides a conceptual understanding of how workers are both disciplined and exert agency within global production systems. The study is based on qualitative interviews with stakeholders who are active in both developing and deploying various technologies in relation to migrant labour rights in fisheries, complemented by an extensive review of secondary documentation. The findings indicate that, within this framework, ICTs can be primarily classified into two distinct categories based on their approach to monitoring and observing labour conditions: a) remote monitoring and b) on-board/community-based monitoring and reporting systems. I will argue that the use of such technologies holds significant potential for advancing transparency and accountability in terms of the labour rights and working conditions of fishing crews. In this way, new possibilities for labour agency and the re-regulation of labour regimes in global production are being opened up, while, at the same time, limitations on the application of ICTs still remain.
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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 | 0.018 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.022 |
| Scholarly communication | 0.013 | 0.019 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".