Bibliographic record
Abstract
Institutional ethnography (IE) is a method of inquiry that problematizes social relations at the local site of lived experience and examines how textual sequences coordinate consciousness and ruling relations. This article explicates some of the shortcomings of IE, so future institutional ethnographers can work with these. I offer a critical assessment of IE, focusing on its ontology of the social and the issue of truncation, the constitutive hermeneutics of interviewing, and the production of possible subjects in data analysis. The promise of IE is its critique of traditional sociology and introduction of ethnographic practice inquiring beyond nominalism into extra-local social relations that, through texts, govern local action. But IE establishes itself in a binary of emancipation versus regulation, so it is less concerned with its necessary complicity in objectification. IE must continue to be a sociology of possibilities, open to its own contradictions and continual reflexive intervention into itself.
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 | 0.063 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.013 | 0.223 |
| Scholarly communication | 0.021 | 0.022 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".