Surrogate Ethnography: Fieldwork, the Academy, and Resisting the IRB
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Nearly every ethnographer has observed the growing reach and increasingly uncomfortable power of the IRB. As IRB restrictions have grown tighter, the consequences have become more dire. The failure of most IRBs to understand ethnography at all, along with increasing concerns about litigation that trump the welfare of both researchers and “subjects,” and the usurping of faculty power by the administration in universities, has left us with a difficult challenge: how can ethnographers and participant observers continue to do their research, without losing their jobs? This paper introduces a new methodology (“surrogate ethnography”). We posit that surrogate ethnography provides three distinct benefits: (1) it represents a methodological and ethical resistance to excessive IRB control, (2) it can help us rescue ethnography and participant observation—at least in a certain form—from IRBs, and (3) it addresses some of the longstanding concerns with autoethnography by proposing an alternative reflective analytic approach to one’s experiences in the field. We share the results of our initial foray into surrogate ethnography, offering our analyses of each other’s stories (one from volunteer work in a prison, and one from participation in sadomasochism/BDSM) in the context of constraints and challenges facing ethnographers in the current academic climate.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.035 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it