The Role of Physiology, Affect, Behavior and Cognition in Leader Character Activation: A Music Intervention
Bibliographic record
Abstract
We build on the theoretical model proposed by Crossan et al. (2021) to examine leader character activation, through the use of music, as a foundational area for leader character development. Our findings reveal that music influences all of the physiology, affect, behavior, cognitive (PABC) systems to more and less degrees. As well, music activates all dimensions of character, with different dimensions of character varying in their reliance on the PABC systems. Our empirical examination underscores the importance of examining activation as an initial step in development, yielding insights into the holistic role of the PABC systems in character development. Although all four systems are implicated, this study points to the need to understand how various dimensions of leader character rely differentially on the PABCs, which provides important insight into how leader character development can be tailored. Finally, the study verifies the important role of music therapy in the activation and subsequent development of leader character and paves the way for other innovative approaches that move beyond the cognitive and behavioral focus in leadership development to embrace physiology and affect as well.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".