The ‘actualities’ of knowledge work: an institutional ethnography of multi‐disciplinary primary health care teams
Bibliographic record
Abstract
This study is set against the backdrop of the evolving order of a health care system in a province implementing a set of concurrent reforms. The study investigates how 'knowledge work' of multi-disciplinary health care teams is actually done and how it is co-ordinated across sites. Knowledge work involves three processes: the creation of new knowledge during the transfer of knowledge, in the context of the application of knowledge to their collective clinical decision-making. Institutional ethnography is used to explore the social and institutional forces that shape the knowledge work of health care providers in and across multi-disciplinary teams by way of examining how the texts trans-locally organise the formation and functioning of multi-disciplinary teams. The study confirms that in the course of their collective clinical decision-making, teams' dialogical exchange facilitates the articulation of tacit knowledge and opens up the communicative space for the creation of new knowledge. In addition to this confirmatory finding, the study contributes to the existing health-related knowledge management by illustrating the importance of the social, communicative aspects of the knowledge processes, and in particular, the relationship between knowledge and the social organisation of power.
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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 | 0.016 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.015 | 0.020 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".