Bibliographic record
Abstract
The iconography of the African AIDS orphan, captured in National Geographic–style images of half-starved toddlers with distended bellies, inspires humanitarian aid for the continent. In Botswana, stereotypes underlying both foreign-funded and governmental programs for orphaned children—which imply that orphans are underfed and underloved—initially resonated with Tswana people’s anxieties that neglect by overburdened kin results in parentless children going hungry. However, during the past decade international feeding projects began to evolve into elaborate day-care complexes in which village orphans gained exclusive access to swimming pools, DVDs, trendy clothing, and daily meat rations. This article traces the shifting moral semiotics of orphans’ fat and skinny bodies, explaining why new discourses protesting the overfattening of orphans arose in a southeastern village. Metaphors of fat and feeding have become a scale on which the excesses of humanitarian aid and the perceived shortcomings of local kinship practices are weighed. A new kind of “politics of the belly” calls into question relations of patronage around metaphors of fleshiness and dependence on foreign support. In the process, contestations over children’s skinny and fat bodies lead to reconfigurations of the idea of orphanhood.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.029 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".