On standpoint, agency and participatory commitment in research:Exploring potentials in institutional ethnography
Bibliographic record
Abstract
In the Nordic countries Institutional ethnography (IE) presents a fairly new approach to qualitative welfare studies ‘from below’. IE is founded by the Canadian critical, feminist sociologist Dorothy Smith with a commitment to do research with people and for people – and see people as knowers of their lives and work - broadly understood. The intention of much IE is thus to present researchers with a methodology or rather an approach (a sociology) to map the institutional coordination and the ‘ruling relations’ of societal structures and discourses - but as they appear in the everyday lives of people at work or as citizens/clients/users/pupils (etc.) of the institutions in view. This keynote outlines the understandings of the idea of standpoint in the Institutional Ethnographical tradition, while also discussing and challenging the capacity of IE framework and methodology, to further the insights of researchers to gain a more nuanced and perhaps optimistic view of people as knowers and learners dealing with their institutional lives in competent ways. I will also discuss ways of supplementing vital institutional insights with other understandings and approaches to peoples’ experiences and their ways of dealing with and learning throughout their institutional lives
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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 | 0.090 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.018 | 0.119 |
| Scholarly communication | 0.024 | 0.030 |
| Open science | 0.003 | 0.024 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".