Bibliographic record
Abstract
Institutional ethnography (IE) is a method of inquiry advocated by Canadian sociologist Dorothy E. Smith and a wide range of researchers working in sociology, social work, education, nursing, political organizing, social policy, women’s organizations, and so on. Institutional ethnographers do not cede authority to ideas established in the literature. Instead, they rely on people’s experience as the point of entry into inquiry exploring connections among local settings of people’s everyday lives, institutional processes, and translocal ruling relations. Smith’s concept of ‘ruling’ is derived from Marx. IE relies on a theorized way of exploring ruling practices—as people’s social activities organized through texts, language and expertise. This article defines some of the concepts of which newcomers to institutional ethnography need to develop a working knowledge, namely: epistemology (and epistemological shift), ontology (and ontological shift), social organization, social relations, ruling relations, the role of texts in ruling relations, ideology, problematic, discourse, experience as data, interviewing, and data collection.
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 | 0.042 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".