Exploring the applications of U.S. Army leader development model in nonmilitary organizations: Implications for training
Bibliographic record
Abstract
The United States Army’s leader development program offers new opportunities to examine how leaders are developed within the traditional workforce. Leader development is at the forefront of Army training and is coordinated through an institutional, operational, and self-development domain. Each domain contributes toward a holistic leader development program which prepares soldiers to be lifelong leaders. Veterans transitioning out of the military are often credited as possessing the leadership skills employers seek, though exploration of the process used to develop leadership attributes in soldiers has been minimal. Upon comparing the Army’s leader development program with other private sector leadership development training, similar goals were identified though the Army’s approach is distinguishable. This paper is an analysis of the U.S. Army’s leader development process and makes comparisons with leadership development in the traditional workplace. Three propositions are presented and discussed for leadership scholars and practitioners to consider. The authors also call for increased research and exploration of leader development in the military for transferability into the traditional workplace.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".