Putting our bodies on the line: Corporeal ethnography and metamorphosis
Bibliographic record
Abstract
With notable exceptions, ethnographers engaging in observant participation have not reflected on what it means to become the object of inquiry. Very little scholarly engagement has focused on the longer-term implications for such becomings for the ethnographer. In the current article, we draw from field notes and broader reflections on our ethnographic experiences, as a cis gender male participating in mixed martial arts and as a cis gender female participating in correctional officer training, to theorize what metamorphosis means for our understandings of our respective fields and our day-to-day lives as academics. We analyze how metamorphosis is experienced differently for our respective genders, and the marks our ethnographic experiences have left on our selves and bodies. The current article is intentionally heuristic, pushing ethnographers to reflect on what ethnography means and the broader effects of ethnographic experiences on our bodies and on our selves.
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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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.010 | 0.031 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".