Institutional ethnography as a unique tool for improving health systems
Bibliographic record
Abstract
Qualitative research in the health system has made tremendous developments in the last decade to better understand patient experiences. What is often overlooked, are the influences that the internal structures, policies and people have on the individuals that use health services. Institutional ethnography is a qualitative approach that aims to capture the social organization of "everyday life" at various system levels. An institutional ethnographic framework was applied to two research studies exploring how families experience care in neonatal intensive care units. Data were collected to develop a deep understanding of the social contexts that exist within institutional boundaries. This paper provides evidence that how care is organized and delivered can significantly influence patient experiences, perceptions and ultimately health outcomes. Adopting institutional ethnographic techniques as a common research method is a valuable tool for health leaders seeking to understand and develop recommendations for health system reform.
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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 | 0.128 | 0.107 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".