Bibliographic record
Abstract
Research on institutional logics has exploded in the last decade. Much of this work has taken its inspiration from Friedland and Alford’s call to “bring society back in” to organizational analysis. Interestingly, when Friedland and Alford published their seminal piece, another body of work with similar focus emerged in France under the banner of French Pragmatist Sociology. In this article, we discuss how French Pragmatist Sociology complements institutional logics by helping it address its main limitations or blind spots. These include (a) microfoundations and recursiveness (how institutions are formed, maintained, or changed at a micro level), (b) legitimacy struggles (how struggles are resolved on a day-to-day basis), (c) morality (as an important element underscoring institutional logics), and (d) materiality (as physical and tangible instantiations of logics). We conclude by suggesting that a rapprochement between both approaches provides an elegant means of bridging the lingering divide between “old” and “new” institutionalism.
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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 | 0.017 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.078 |
| Scholarly communication | 0.020 | 0.022 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".