‘The land is now not fertile’: social landscapes of hunger in south-eastern coastal Tanzania
Bibliographic record
Abstract
Based on ethnographic fieldwork in a coastal village in south-eastern Tanzania, this paper examines how social inequalities and social suffering become embodied in the lived experiences of hunger. The paper explores local meanings of food, fertility and hunger and how these concepts interconnect and materialize on a landscape impacted by two large-scale conservation and development projects, the Mtwara Development Corridor and the Mnazi Bay Ruvuma Estuary Marine Park. Fourteen in-depth interviews Sinde villagers were conducted to elicit narratives about their food experiences in addition to 24 hour food recall and pile sort to explore local taxonomies of food. One focus group discussion with six women was also conducted. The study finds displacement from resources by the conservation and development projects has exacerbated existing food security issues of irregular rains, increasing food prices and malnourished bodies. The downward cycle of food insecurity has local villagers worried about the viability of their community's future, embodied in the health of local children and their performance in school. Increasing food insecurity is internalized within the community as infertility where the health of the landscape is connected to the health of society.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 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 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".