The Heart of Institutions: Emotional Competence and Institutional Actorhood
Bibliographic record
Abstract
We develop the concept of emotional competence, which refers to the ability to experience and display emotions that are deemed appropriate for an actor role in an institutional order. Emotional competence reveals a more expansive view of emotions in institutional theory, where emotions are central to the constitution of people as competent actors and lend reality and passionate identification to institutions. We distinguish two facets of emotional competence—private, which is needed to engage in self-regulation, and public, which is needed to elicit other-authorization—and two criteria for assessing emotional competence—the deemed naturalness and authenticity of emotions within an institutional order. These distinctions delineate four processes through which emotional competence ties personal experience and social performance to fundamental institutional ideals, the institution’s ethos. We discuss theoretical and methodological implications of this model for researching institutional processes.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.028 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| 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".