The ‘other’ within: Striving for health equity in the Maldives Eva-Maria
Bibliographic record
Abstract
Relations within are quintessential in anthropological fieldwork — and in archipelagos in particular. The domestic sea is incorporated in the national consciousness connecting an archipelagic nation but distinguishing individual islands with a strong emphasis on the centre. The Maldivian archipelago displays this spatial organization of a socio-political and economic centre and a dependent island periphery. In the national consciousness, the capital island, Male', contrasts with “the islands” — a distinction which is particularly evident in the public health sphere, where striving for health equity encounters geographical and socio-political obstacles. Using the topic of the inherited blood disorder thalassaemia as a magnifying lens, this paper asks how different actors are making sense of health inequities between central and outer islands in the Maldivian archipelago. Intra-archipelagic and international mobilities add to the complexities of topological relations, experiences, and representations within this multi-island assemblage. Yet, my study of archipelagic health relations is not confined to a mere outside look at the construction of the ‘island other’ within the archipelagic community. It is a situated investigative gaze on disjunctures, connections, and entanglements, reflecting my methodological-theoretical attempt to unravel my own involvement in island–island relations and representations — my being entangled while investigating entanglements.
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 | 0.004 | 0.004 |
| 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 | 0.012 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 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".