A cultural landscape approach to community-based conservation in Solomon Islands
Bibliographic record
Abstract
International environmental organizations have an increasing commitment to the development of conservation programs in high-diversity regions where indigenous communities maintain customary rights to their lands and seas. A major challenge that these programs face is the alignment of international conservation values with those of the indigenous communities whose cooperation and support are vital. International environmental organizations are focused on biodiversity conservation, but local communities often have a different range of concerns and interests, only some of which relate to biodiversity. One solution to this problem involves adoption of a cultural landscape approach as the ethical and organizational foundation of the conservation program. In our conservation work in coastal Melanesia, we have developed a cultural landscape approach that involves the construction of a conceptual model of environment that reflects the indigenous perceptions of landscape. This model incorporates cultural, ideational, and spiritual values alongside other ecosystem services and underpins the conservation activities, priorities, and organizational structure of our programs. This cultural landscape model was a reaction to a survey of environmental values conducted by our team in which Solomon Islanders reported far greater interest in conserving cultural heritage sites than any other ecosystem resources. This caused a radical rethinking of community-based conservation programs. The methodologies we adopted are derived from the fields of archaeology and historical anthropology, in which there is an established practice of working through research problems within the framework of indigenous concepts of, and relationship to, landscape. In our work in Isabel Province, Solomon Islands, coastal communities have enthusiastically adopted conservation programs that are based on cultural landscape models that recognize indigenous values. A particularly useful tool is the Cultural Heritage Module, which identifies cultural heritage sites that become targets of conservation management and that are used as part of a holistic framework for thinking about broader conservation values.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.015 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".