Sustainable Livelihoods of Fishermen Households Headed by Women (Case Study in Riau Islands Province of Indonesia)
Bibliographic record
Abstract
The number of fishing households headed by women continues to show improvement in the last decade. In Riau Islands Province Indonesia, showed more than 80 % are coastal villages with most of the poor people, and more than 50 % of the poor are women who are vulnerable social economic will be head of household. This study focuses on five dimensions of livelihood assets to find the status of sustainability. The questionnaire survey addressed to 29 fishermen households headed by women from 300 fishermen households in the Malangrapat village. The results of this study highlight how the dimensions of personal leadership assets showed the main actors to influence the sustainable livelihoods in fishing households headed by women. Strengths of personal and leadership assets of women in the household could be an important factor to consider in agricultural development and fight against poverty in the rural areas, because by having good personal leadership they have a strong motivate to get out of poverty through women. This showed by the index of the personal and leadership assets dimensions of sustainable enough (60.34 and 71.93), while the other dimension does not show sustainability; social assets (26.87), human resources assets (27.59), financial assets (31.86), and physical assets (36.38).
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".