FINDING THE COMMUNITY IN COMMUNITY-BASE NATURAL RESOURCE MANAGEMENT: THE CASE OF NDUMO GAME RESERVE, SOUTH AFRICA
Bibliographic record
Abstract
In South Africa Community-based Natural Resource Management (CBNRM) has recently gained popularity as the dominant approach to conservation due to its perceived environmental and social benefits and as a form of restitution for communities that were forcibly evicted from their land during apartheid. This dissertation investigates the disconnect between the rhetoric and reality of CBNRM in South Africa, by focusing on the case of Ndumo Game Reserve. It aims to critically evaluate the social justice and economic impacts of CBNRM on the neighbouring Mbangweni and Mathenjwa communities. It argues that there are significant tensions between the community focused rhetoric of CBNRM, the predominantly fortress-style of conservation, and the neo-liberal eco-tourism venture at Ndumo Game Reserve. I conclude that CBNRM at Ndumo is largely guided by western conservation and economic ideologies and driven by the support of state and private interests while alienating local people from their land and its management.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.047 | 0.023 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 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".