Professionals and field-level change: Institutional work and the professional project
Bibliographic record
Abstract
This article explicates the causal connections between changes in professional jurisdictions and changes in organizational fields. The authors argue that professional projects carry within them projects of institutionalization. They focus attention on the critical but often invisible role that professionals play in institutional work, or the creation, maintenance and transformation of institutions. The key contribution of this article is to explicate the professional project as an endogenous mechanism of institutional change. Based on a review of prior research on institutional change in which professionals play a central role, the authors observe four essential dynamics through which professionals reconfigure institutions and organizational fields. First, professionals use their expertise and legitimacy to challenge the incumbent order and to define a new, open and uncontested space. Second, professionals use their inherent social capital and skill to populate the field with new actors and new identities. Third, professionals introduce nascent new rules and standards that recreate the boundaries of the field. Fourth, professionals manage the use and reproduction of social capital within a field thereby conferring a new status hierarchy or social order within the field.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.009 | 0.053 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".