Bibliographic record
Abstract
While anthropology students may receive general instruction in the debates and critiques surrounding public and/or engaged anthropology, attention to the growing intersection between participatory action research (PAR) and anthropology is often overlooked. I contend that to think of PAR as a complementary approach to conventional anthropological fieldwork (i.e. interviews, participation observation, and focus groups) is problematic in that it runs counterintuitive to the former’s transformative logic. Drawing from my work co-leading a radio-based partnership project with urban Inuit organisations in Montreal and Ottawa, I repurpose Sol Tax’s ‘action anthropology’ to discuss an attitudinal shift that our team’s use of PAR has provoked, reconceptualising the aims and practice of our ethnographic enquiry in the process. I consider the effects of this shift for anthropological training and pedagogy in PAR projects and propose the use of ‘training-in-character’ as an organising principle for the supervision of student 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 | 0.023 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.060 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".