The Hybridisation, Resilience, and Loss of Local Knowledge and Natural Resource Management in Zambia
Bibliographic record
Abstract
Abstract The contribution of Indigenous and local knowledge (ILK) to natural resource management has recently gained increasing prominence in academia, policymaking, and civil society. However, persistent knowledge gaps concerning the contribution of ILK to sustainable landscape management remain. We investigate existing local knowledge and practices of the Tonga of Kalomo District, Zambia, and their contribution to sustainable landscape management by combining walking interviews with photovoice. Especially Tonga women and youth are important knowledge holders for land management, agricultural practices, and tree conservation. We found that local knowledge is often ‘hybridised’ with ‘external knowledge’ when local knowledge alone is deemed insufficient. In some cases, introduced ‘external knowledges’ are simply reconstituted long-standing local practices. Nevertheless, local communities often perceive external knowledge holders as “knowing better.” Finally, we show how local knowledge and associated practices have been simultaneously eroded and lost and describe those that have remained resilient to provide insights into the complexity of hybridisation processes where different knowledge systems interact.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".