Human Resource Development Review / December 2002 Drodge, Murphy / EMOTIONS IN POLICE LEADERSHIP Interrogating Emotions in Police Leadership
Bibliographic record
Abstract
Theoretical discourse about leadership was traditionally conceived as a rational process of social action emanating from a leader whose traits were deemed largely responsible for the success or failure of the organiza-tion. The role of emotions in leadership, when they were discussed at all, tended to be viewed either negatively as irrational dimensions of mind interfering with the rational business of leading or as a discrete psycho-logical category subsumed within emotional intelligence. In this article, the authors conceptualize emotions holistically as an embodied phenome-non that mediates the social process of leadership. They discuss police leadership as a specific organizational context that shapes and constrains emotional expression and suggest ways that emotional intelligence might be construed to aid police leadership development. Leadership ranks among the most researched and debated topics in the social sciences (George, 2000). Recently, police organizations have suc-cumbed to the allure of leadership as a topic of discussion and research (Adlam, 2001; Kobe, Reiter-Palmon, & Rickers, 2001). In some countries, Canada for instance, the expected exodus of senior police leaders as baby boomers retire en masse lends a sense of urgency to the issue of leadership succession planning and development. At a practical level, identifying who may be a good police leader and defining the characteristics of effective police leadership remain a challenge. However, the broad topic of leader-ship is even more problematic if one considers the theoretical heterogeneity of the field (Yukl, 2002) and the deeper question of defining leadership (Barker, 2001). In this article, we fuse our interest in police leadership to our understanding of contemporary theorizing and research on the topic of emotions. Correspondence concerning this article should be addressed to Edward N. Drodge, HR Research and
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.006 |
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".