Relational values of forests: Value‐conflicts between local communities and external programmes in Sulawesi
Bibliographic record
Abstract
Abstract Studies found that rapid decline of biodiversity and ecosystems globally have adversely affected an estimated 1.6 billion rural people whose livelihoods both directly and indirectly depend on forests. To halt the loss of forests and other natural ecosystems that simultaneously support rural livelihoods, various external programmes have been developed and applied, including market‐based and rights‐based approaches. However, rapid biodiversity and ecosystem decline continues, and better incentives or more secure rights have not always led to local community participation and improved livelihoods. This suggests the need to better explain local communities' motivations in nature stewardship. We conducted a study of local communities in two villages in Sulawesi who voluntarily maintain forests but showed resistance to participation in formal Social Forestry programmes. The study aimed to identify motivations and underlying reasons of community preferences, guided by two research questions: (i) how did local people value forest landscapes? and (ii) how did those values interact with externally driven Social Forestry programmes? We applied the Relational Values concept to understand a community's relations with the forest (or its elements) and land and identified points of value divergence. Data collection involved in‐depth semi‐structured interviews, focus group discussions framed by the principles of Appreciative Inquiry, participant observation and land use/land cover change analysis. Our findings show that people value their forests in relation to their identity, ancestral heritage, sense of place and spiritual values. We also identified the points of value divergence and their underlying reasons of resistance towards externally driven forestry programmes. This study thus contributes to the broader conceptualisation of values in conservation and community participation by providing empirical evidence on the importance of the Relational Values framework in understanding the motivation and behaviour of nature stewardship and in the evaluation of value conflicts. Read the free Plain Language Summary for this article on the Journal blog.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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".