Bibliographic record
Abstract
Instead of focusing on dominant institutional logics to understand institutional change, we develop the concept of a constellation of logics (professional, market and organizational logics). We analyze changes in the US pharmacy organizational field, showing that a changing constellation of logics is consistent with the nature of work and organizing principles for the field. Early neoinstitutional work sought to explain stability, convergence, and isomorphism in organizational fields. In recent years, however, there has been increasing interest in understanding how organizational fields change over time. Within this relatively new focus on institutional change, a focus on institutional logics has become increasingly prevalent. Logics are the “organizing principles ” that shape and constrain the behavioral possibilities of actors (Friedland & Alford 1991). Logics specify what goals or values are to be pursued within a given domain and what means are appropriate for pursuing them (Scott et al. 2000). In most instances, fields are depicted to have a dominant or prevailing logic, although other logics may exist. It is generally accepted that as an organizational field undergoes a “profound institutional change ” it transitions from one dominant logic to another (Scott et al., 2000: 24). For example, Thornton (2004)
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.705 | 0.362 |
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".