Assessing long-term conservation impacts on adaptive capacity in a flagship community-based natural resources management area in Botswana
Bibliographic record
Abstract
Over the past three decades community-based natural resources management (CBNRM) has sought to address the concurrent needs of economic development and ecological protection at the local level, but there is often strong divergence between development and conservation interests and successes. In particular, CBNRM has not always led to expected socioeconomic outcomes, while information of its impact on human well-being at household level is sparse. In Botswana, most communities do not disburse benefits from CBNRM ventures to households. This leads to an inherent scale mismatch that arises because the costs of living with wildlife are felt at the household level, while the benefits are paid out at the community or village level. We use longitudinal data from two household surveys conducted 22 years apart to assess if benefits from the Botswana model of CBNRM have increased household-level adaptive capacity for those living with wildlife. We take a livelihoods capital approach to develop indicators of adaptive capacity and measure how livelihood diversity, inequality, and adaptive capacity have changed in five communities in northern Botswana between 1995 and 2017. Our analyses confirm the findings of qualitative reviews and suggest that CBNRM is under-performing in its contribution to improved household-level adaptive capacity. CBNRM cannot be said to benefit communities if the majority of community members do not experience increased well-being. We therefore recommend restructuring the governance models of CBNRM and other community conservation approaches to ensure that benefits are more directly targeted to actively participating households.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".