Notes on an archipelagic ethnography: Ships, seas, and islands of relation in the Indian Ocean
Bibliographic record
Abstract
This paper explores a mobile anthropological method, or what I call an archipelagic ethnography. This archipelagic ethnography focuses on relationality to think through not only islandness and archipelagoes—land, ship, and sea—but also considers relationality as a starting point for examining connections across space. Based on over ten years of ethnographic research among dhow sailors in the Indian Ocean, I argue that navigation, social interactions, notions of patronage, and protection alongside memories and histories of mobility draw together these multiple spaces across the Indian Ocean. Moving between dhows docked in port, on islands, and at sea, I elaborate on an archipelagic ethnographic method that is a mode of thinking relationally about different kinds of spaces and places. Taking relationality as a central point in thinking through relations between ship, land, and sea, I hope to think about the notion of society in relational terms as a starting point for an anthropological method that is attuned to both difference and connection.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.017 | 0.023 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".