Bibliographic record
Abstract
Abstract In her 1973 article “up the anthropologist” Laura Nader called on anthropologists to engage in critical studies of the relationship between powerful institutions and the broader society, using a “vertical slice” approach. But Nader worried that participant observation was hard in the context of studying up, and yet it has been presented as definitive of anthropology’s methodology. This article discusses four methodological strategies for studying up in the light of this concern: insider ethnography; covert ethnography; remote ethnography; and adapted participant observation. The first two have intellectual or ethical liabilities. The last is increasingly normalized. Going forward, anthropologists studying up face two obstacles: first, the increasingly totalizing hold of corporate and government workplaces over their employees, even when they are not at work; and, second, university institutional review boards (irb s) concerned to avoid conflictual or critical research.
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 | 0.117 | 0.127 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.011 | 0.071 |
| Scholarly communication | 0.020 | 0.056 |
| Open science | 0.007 | 0.047 |
| Research integrity | 0.006 | 0.016 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".