Leadership Development in the Ecuadorian Military: Conversations with Members of Elite Units
Bibliographic record
Abstract
Militaries around the world are studying leadership and consider that leadership training is giving them an advantage both on and off the battlefield. As the first ever research into leadership within the Ecuadorian military, the intent of the present study was to have military personnel explore their personal leadership and discuss individual and institutional ways to increase capacity. Empirical data was collected from men in the Anti-terrorism Special Forces and Intelligence Units of the Ecuadorian Army and from the Peacekeeping School which has military personnel from all three arms of the military, army, navy and air force. In addition, action research in the form of an Interview Matrix Activity and World Café were conducted with the Anti-terrorism Special Forces Unit. Research results were identified. Eight recommendations emerged from these findings that may assist the Ecuadorian military in taking steps to implement foundational leadership training.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.005 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".