Peran Perempuan dalam Perekonomian Lokal Melalui Ekowisata di Maluku: Tinjauan Sosio-Ekologi dan Sosio-Ekonomi
Bibliographic record
Abstract
This research aims to describe the role of women in Maluku, particularly in the tourist destination of Negeri Hukurila Beach, in the local economy through ecotourism with a socio-ecological and socio-economic approach. Through this analysis, we aim to understand the contributions of women in maintaining the sustainability of the natural environment and promoting local economic development. The research findings indicate that women in Maluku possess rich ecological knowledge and play a crucial role in preserving the natural environment in this region. They actively engage in various aspects of ecotourism, such as guiding tours, managing local eateries, producing traditional handicrafts, and operating homestays. Their contributions in these sectors not only add value to the tourist experience but also have a positive impact on the local economy. Additionally, women in Maluku have the potential to strengthen their role in decision-making related to ecotourism development. By actively participating in the planning and management of local resources, they can play a key role in formulating policies that support sustainable development. The research also reveals that women in Maluku play a crucial role in raising public awareness about marine conservation. Concrete actions, such as maintaining beach cleanliness, anti-littering campaigns along the coast or rivers, and encouraging fishermen to use sustainable fishing techniques, are integral parts of their efforts to build awareness about the importance of preserving the marine environment. Thus, this research concludes that women have a significant role in ecotourism in Maluku, both in socio-ecological and socio-economic terms.
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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 | 0.000 | 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".