Climate stressors, food security, and participation decisions among women in seafood production systems
Bibliographic record
Abstract
If properly managed, seafood production systems can provide a sustainable and climate-resilient source of nutrient and protein-rich food and employment for millions of people in coastal communities. However, seafood is declining due to myriad social, economic, and climate change stressors, affecting fishery-based livelihoods and the decision for some actors to continue harvesting. This study uses the case of small-scale women oyster harvesters in The Gambia to assess how fishery-based livelihood activities, climate stressors, climate adaptation, and household food security influence surveyed respondents' willingness to continue harvesting. Cross-sectional data were collected from 357 women oyster harvesters in 16 oyster communities in The Gambia. We show a negative association between willingness to continue with women oyster harvesters’ perception of increasing temperatures, increasing storms, and decreasing rainy days over a 5-year recall period. Similarly, we show a negative association between women oyster harvesters’ willingness to continue and food-insecure households. Meanwhile, a positive relationship was established between respondents' willingness to continue and participation in planting mangrove trees as a climate adaptation strategy. This study advances the argument for the need to pay attention to challenges facing seafood production systems and their sustainability now and in the future. The empirical evidence highlighted in this study provides a strong rationale for policies, strategies, and interventions that support climate-resilient seafood production systems, livelihood diversification, and food security in The Gambia and other developing countries.
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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 | 0.002 | 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 | 0.000 | 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".