Employment Practices, Cost Minimization, and Their Implications for Food Provisions and Seafarers’ Wellbeing on board Ships – A Qualitative Analysis
Bibliographic record
Abstract
The global shipping industry, responsible for delivering over 70% of the world’s goods (in volume), has increasingly adopted cost minimization policies, contributing to precarious employment practices that adversely affect seafarers’ wellbeing. This study focuses on the intricate relationship between employment precarity and food provision on cargo ships. By presenting seafarers’ perspectives, we aim to understand how precarious employment practices and cost minimization in the industry influence power dynamics related to food and impact seafarers’ wellbeing. Drawing on empirical data collected through shipboard observations and interviews with seafarers, this study examines the often-overlooked experiences and perspectives of seafarers. The research sheds light on the precarity of employment in shipping and its inherent impact on the provision of food on board and its implications for seafarers’ physical and emotional health, including the availability of nutritious and sufficient food and its impact on their daily lives. Through in-depth interviews, seafarers’ insights into their experiences of food including the quality, availability, and cultural appropriateness of food on board are explored, as well as the standard of training for cooks. Through this research, we found substandard conditions on some of the ships, cost-focused decision-making, and lack of standardized food preparation practices on board. These findings underline the need for improved regulations, better training opportunities, and increased consideration for seafarers’ wellbeing. These changes are essential to ensure the provision of adequate and nutritious meals that promote the physical and mental health of seafarers on board ships. Specifically, the research underscores the need for policy and advocacy initiatives to improve seafarers’ lives and promote fair working conditions in the global shipping industry. By amplifying the voices of seafarers and providing evidence-based insights, this study contributes to the larger discourse on workers’ rights and the importance of decent working conditions. It calls for greater attention to the provision of adequate, nutritious, and culturally appropriate food on board cargo ships, recognizing its significance for seafarers’ physical and mental wellbeing, as well as a call for standardized training for ship’s cooks.
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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) | 0.000 | 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".