Manning the mangroves: gender, regional identities, and social history shape mangrove forest dependence and governance
Bibliographic record
Abstract
Fuelwood, a forest resource, is used to satisfy local energy demands in many parts of the world. However, wood harvesting for subsistence or livelihood dependence is challenged by conservation narratives of forest degradation and loss in many parts of the Global South. Despite a vast network of protected areas that regulate access to resource extraction, forest dependence continues. Simultaneously, wood fuel continues to be used as a renewable source of energy in many developed countries. Energy transitions and the adoption of cleaner or low-carbon fuels are deeply socio-political and embedded in gender and social inequalities. Fuelwood dependence and adoption of alternate low-carbon technologies impact gender and social equity in intersectional ways. This study investigates the drivers of forest dependence on fuelwood and how that relates to broader narratives of forest degradation and conservation in Bhitarkanika National Park, a protected mangrove forest along the east coast of India. It utilizes the theory of access with surveys and focus groups to inquire about the socio-cultural beliefs and influences that shape reliance on firewood. Additionally, it also examines how access contributes to constraining or intensifying forest dependency, and how this dynamic interacts with intersectionality to uphold prevailing social conditions. The findings reveal a gendered differentiation in labor and values toward fuelwood collection and use. Women were found to be reluctant to change traditional ways of cooking and heating because of social responsibilities, structures, and preferences whereas men supported alternatives to fuelwood use, implying an invisible burden of conservation on women. Although forest dependence was largely for fuelwood, these dependencies stemmed from both social and cultural preferences, affirming the requirement for integrating cultural preferences and values that shape communities reliant on mangrove forests, to effectively devise practical conservation solutions involving alternative technologies or subsidized fuel options.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".