Gender dynamics, climate change threats and illegal, unreported, and unregulated fishing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The persistent challenge of gender inequality continues to shape socio-economic dynamics within small-scale fisheries, creating complex cycles of vulnerability for both women and men. Contemporary policy interventions frequently fail to address the gender mechanisms that underpin these vulnerabilities, thereby overlooking critical opportunities for promoting equity and resilience. This study examines the multifaceted intersections of gender with environmental and social stressors, specifically focusing on climate change and illegal, unreported, and unregulated (IUU) fishing in small-scale fisheries. By synthesizing 189 peer-reviewed publications, this research highlights the disproportionate burdens experienced by women within maritime socio-ecological systems. The findings reveal how structural barriers systematically constrain women's adaptive capacities, while simultaneously demonstrating the potential of gender-responsive strategies to enhance community resilience. The analysis argues that integrating gender considerations into fisheries governance is not merely an ethical imperative but a fundamental requirement for addressing the interrelated challenges of environmental change and maritime resource management. Graphical Abstract
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it