Transformational and active transactional leadership in the Canadian military
Bibliographic record
Abstract
Purpose This study seeks to examine the manifestation and effects of transformational, contingent reward, and active management‐by‐exception leadership across ranks in the Canadian military. It also aims to investigate whether or not the relationships between perceived leadership behaviors and effective leadership outcomes are moderated by hierarchical level and followers' expectations. Design/methodology/approach A total of 704 military officers and enlisted members rated their leaders' behaviors and the behaviors they expect of their leaders. Findings Frequency of transformational leadership behaviors increased with rank, but frequencies of perceived and expected contingent reward and active management‐by‐exception leadership behaviors did not. Transformational and contingent reward leadership effects were not moderated by rank or by followers' expectations. The effects of perceived active management‐by‐exception leadership were moderated by followers' expectations. Research limitations/implications When followers do not expect active management‐by‐exception from their supervisors, based on their own implicit beliefs about the types of behaviors their leaders should be exhibiting, but they are subjected to it, their job satisfaction and their attitudes toward their supervisors may be negatively affected. Practical implications Transformational leadership is prevalent, expected, and effective at all hierarchical levels. Because of their positive impact on followers' job satisfaction and their attitudes toward their supervisors, the Canadian military should continue to encourage transformational leadership and contingent reward leadership behaviors at all hierarchical levels. Originality/value The study highlights the potential importance of congruence between the expectations followers have of their leaders and followers' perceptions of their leaders' actual behaviors.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".