Look What's Back! Institutional Complexity, Reversibility and the Knotting of Logics
Bibliographic record
Abstract
Through a comparative historical study of community pharmacy in the UK, Italy, Sweden and the USA, the authors examine what happens to institutional arrangements designed to resolve ongoing conflicts between institutional logics over extended periods of time. It is found that institutional arrangements can reflect the heterogeneity of multiple logics without resulting in hybridization or dominance. Because logics remain active, similar conflicts can reappear multiple times. It is found that the durability of the configurations of competing logics reflects the characteristics of the polities in which fields are embedded. The dominance of any societal institutional order leads to more stable field‐level arrangements. The authors suggest that the metaphor of institutional knots and the related image of institutional knotting are useful to capture aspects of this dynamic and to foreground the discursive and material work that allows multiple logics to coexist in local arrangements with variable durability.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.047 |
| Scholarly communication | 0.013 | 0.022 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".