Perspectives on and From Institutional Ethnography
Bibliographic record
Abstract
This book explores recent developments in Institutional Ethnography (IE) and offers reflective accounts on how IE is being utilised and understood in social research. IE is a sociological sub-discipline developed by Dorothy E. Smith that seeks to explicate the textual mediation of people’s everyday experiences in their local sites of being. As an approach, IE is growing in significance across the globe, particularly in Canada, USA, Australia and UK. \n \nThis collection includes contributions from those involved in the early development of IE alongside Smith as well as early career researchers, new to the sociology, theory and method of IE. Chapters focus on IE as a sociological theory and qualitative research method; the relationship between data generation and analysis in IE; implications from its findings for policy; and IE as a significant methodological approach. This involves explication of the theoretical, the operationalization of IE, and links between the theoretical and the empirical. It illuminates the relationship between data generation and analysis and includes consideration of its own textual relations of ruling
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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 teacher head, 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".