On the Outside Looking In: Ethnography and Authoritarianism
Bibliographic record
Abstract
Despite the common assumption that ethnography is most successful where researchers achieve recognition as insiders within the communities they study, conducting research in nondemocracies inverts incentives to conduct ethnographic research as an insider and poses unexpected ethical risks to both researchers and respondents. Rather than increasing trust and facilitating access, cultivating insider roles in nondemocracies may have the unintended effects of encouraging conformity with regime discourses, limiting further fieldwork access, and exacerbating respondents’ tendency toward epistemic deference. Drawing on the authors’ research experiences and the growing literature on fieldwork in nondemocracies, this article argues that outsider roles may be preferable to insider roles for identifying the unspoken rules, assumptions, and taken-for-granted aspects of everyday politics in nondemocracies. Moreover, outsider roles clarify the relationship between researcher and respondent in ways that provide clear ethical advantages in terms of consent, value, and risk.
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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 | 0.031 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.008 | 0.032 |
| Scholarly communication | 0.008 | 0.010 |
| 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".