A Systematic Literature Review on the Quality of Work Life of Fishermen in Kerala
Bibliographic record
Abstract
This systematic literature review investigates into the Quality of Work Life (QWL) of fishermen in Kerala, India, a region where the fishing industry plays a crucial role in the socio-economic framework. The review identifies and examines the multifaceted challenges impacting fishermen's QWL. These challenges include severe occupational hazards, such as accidents and exposure to extreme weather conditions, and economic uncertainties driven by fluctuating fish prices and rising fuel costs. Environmental concerns, like fish stock depletion and water pollution, further exacerbate their difficulties. Social vulnerability and marginalization, characterized by inadequate healthcare, limited educational opportunities, and insufficient social support, add to their plight. Fishermen also struggle with work-life imbalance due to long hours and irregular schedules, and face technological limitations that hinder productivity. Inadequate government support, limited market access, health issues, and the lack of social security compound these problems. By synthesizing these findings from existing literature, this review underscores critical areas for intervention and policy development to improve the welfare and dignity of Kerala's fishing communities.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.015 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".