Bibliographic record
Abstract
For much of the 20thcentury, indigenous cosmologies, understood as the totalizing worldviews of delimited social groups, were one of ethnology’s central topics. In the last few decades, however, the concept of cosmology no longer sat well with many ethnologists’ wariness of identifying social wholes as analytic units and with accepting correspondences of social organization with orders of time, space, and color, among others. Recently, Allen Abramson and Martin Holbraad, in their 2014 bookFraming Cosmologies, called for a “second wind” of anthropologists’ attention to cosmologies, now including popular understandings of Western science. While endorsing this broadened attention to cosmology and the uses of analyst’s perspectives, I call for remaining attentive to the practical uses of cosmologies by the actors that ethnographers learn from. This entails attending to the social accountabilities and organizational contexts that constrain how people act. I seek to illustrate this by drawing on ethnographies of fishers in south India as well as of astrophysicists in Germany.
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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.010 | 0.049 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.019 | 0.005 |
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".