Strengthening Climate Change Resilience and Adaptive Livelihood for Women’s and Youth in Poso, Central Sulawesi
Bibliographic record
Abstract
This study investigates the challenges of climate change and its disproportionate impacts on marginalized communities in Poso, Central Sulawesi, focusing on sustainable livelihood development. Through the Sustainable Livelihood Framework, Satelite Image Analysis and Theory of Change, the research explores livelihood assets and vulnerability contexts, employing a case study approach in Masani and Lape Villages. Primary data was collected through interviews and focus group discussions, while secondary data was gathered from literature study. Results reveal the challenges regarding livelihood assets which are agricultural productivity problems, limited access to healthcare, and underutilization of natural resources. Proposed strategies to address the challenges include capacity building, post-harvest technology enhancement, home gardening promotion, and agrotourism development. Furthermore, stakeholder collaboration and policy enhancement are vital for effective implementation. Ultimately, the study advocates for better improvement and utilization of livelihood assets through inclusive and adaptive approaches to enhance community resilience and sustainability, empowering marginalized groups for a more prosperous future.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".