Kgalagadi Transfrontier Park and its land claimants: a pre- and post-land claim conservation and development history
Bibliographic record
Abstract
Kgalagadi Transfrontier Park is located in the Northern Cape Province of South Africa and neighbouring Botswana. The local communities on the South African side, the Khomani San (Bushmen) and Mier living adjacent to the park have land rights inside and outside the park. The path from a history of land dispossession to being land owners has created conservation challenges manifested through heightened inter- and intra-community conflicts. The contestations for land and tourism development opportunities in and outside the park have drawn in powerful institutions such as the governments, South African National Parks, private safari companies, local interest groups and NGOs against relatively powerless local communities. This has consequently attracted national and international interest since it may result in further marginalization of the communities who lack the power to negotiate resource access. Moreover, the social and political system of the San is romanticized while little is reported about the Mier, who are an integral part of the park management system. To make these issues more accessible to a growing audience of interested parties and to better understand present conservation and development challenges and opportunities, this paper synthesizes information on the pre- and post-land restitution history of the park and the adjacent communities.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".