Exploring the link between forests, traditional custodianship and community livelihoods: The Case of Nyambene forest in Kenya
Bibliographic record
Abstract
Kenya is home to many sacred natural sites, including forests, mountains and rivers. Indigenous communities have upheld their role and responsibilities, passed down over centuries by their ancestors as custodians of these places through time. The 5391 hectares in the Nyambene forest in central Kenya is a sacred site to the Ameru people, a community/tribe living on the northeastern slopes of Mt. Kenya. The forest is a resource from which customs, spiritual practices, and governance systems are derived to protect the territory as a whole and maintain its order, integrity and well-being. The Njuri Ncheke (council of elders) play a vital role in upholding the traditional ecological knowledge and customs, practised over generations, including acting as custodians of sacred groves around which rain-making rituals are performed. This paper examines the link between traditional custodianship and community livelihoods against a background of diverse national legislations on forest/land use management and religious influences. The author demonstrates how this forest weaves around the lives of the Ameru people and makes a case for the need to encourage community participation and traditional custodianship in protecting ecosystems and their associated cultural heritage.
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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 | 0.002 |
| Science and technology studies | 0.030 | 0.013 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".