Political Ecology of Development In South Africaâs Wild Coast: Exploring Stakeholder Arguments for and Against Possible Development Strategies
Bibliographic record
Abstract
Characterized by scenic beauty and biodiversity, yet impoverished peoples, the Wild Coast of South Africa lies at a development crossroads, whereby various land-use proposals offer different outcomes. This thesis sought to analyze various stakeholder arguments in support of development strategies, especially involving the local people and environment. Based on a document analysis and interviews, the predominant development strategies supported were small community development initiatives (SCDIs) and tourism, supported by NGOs, and mining, supported by the private sector yet opposed by NGOs. A major finding was that while government outlines many development “objectives”, successful results are negligible, suggesting that this sector is an overall ineffective determinant for Wild Coast development. NGO and private sectors provided valid arguments in support of their strategies, leaving the researcher to conclude that means of collaboration should be determined in order to best develop the Wild Coast (via SCDIs, tourism, and mining) and improve local livelihoods.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.016 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".