Leadership and Followership as One
Bibliographic record
Abstract
Many people occupy roles of leader and follower in their jobs and are expected to juggle these effectively. This dynamic is particularly salient in the military, where people often switch between leader and follower roles depending on the situation. In this study, we sought to better understand how members of the military interpret and engage in these 2 roles. We interviewed 10 individuals who were either employed at or attending the Royal Military College of Canada and who held positions encompassing both leadership and followership. Two key themes emerged. First, unexpectedly, we found that members not only recognized the importance of the 2 roles, but also described them in ways that seemed to fuse them together: in other words, leadership and followership were seen as 1. We also found that far from attempting to maintain distance and authority with respect to subordinates and trainees as might have been expected, respondents emphasized mentoring and modeling mechanisms implying closeness and proximity, thus bridging the distance between leaders and followers. Our findings reveal the distinctive form that “connecting leadership” may take in the military. We conclude with a discussion of the transferability of these findings to other settings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".