In a Wounded Land : Conservation, Extraction, and Human Well-Being in Coastal Tanzania
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<div>Global efforts to conserve nature and prevent biodiversity loss have intensified in response to planetary-scale challenges—nowhere more so than in coastal regions. Accordingly, international conservation organizations have increased their efforts to promote marine protected areas as one of the interventions to prevent biodiversity loss in global hotspots.<br><br>Focusing on the human element of marine conservation and the extractive industry in Tanzania, this volume illuminates what happens when impoverished people living in underdeveloped regions of Africa are suddenly subjected to state-directed conservation and natural resource extraction projects, implemented in their landscapes of subsistence. <i>In a Wounded Land</i> draws on ethnographically rich case studies and vignettes collected over a ten-year period in several coastal villages on Tanzania’s southeastern border with Mozambique. In seven chapters, the book demonstrates how state power, processes of displacement and dispossession, forms of local resistance and acquiescence, environmental and social justice, and human well-being become interconnected.<br><br>Written in lucid, accessible language, this is the first book that reveals the social implications of the co-presence of a marine park and a gas project at a time when internationally funded conservation initiatives and extraction projects among rural African populations are engendering rapid social transformation.<br>&nbsp;</div>
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.015 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it