Air Force Deployment Reintegration Research: Implications for Leadership
Bibliographic record
Abstract
Expanding on previous research on the reintegration experiences of Army Augmentees (Thompson & Gignac, 2001), this study investigated the post-deployment reintegration issues and experiences of a sample of 95 Canadian Air Force personnel posted at seven different Air Force bases across Canada. A total of 14 semi-structured focus groups were held. The purpose of the present report is to detail some of the leadership issues that Air Force personnel identified as important in the context of multidisciplinary teams and teams formed with augmentees. These included leadership issues in team formation (i.e., choice vs. coercion, identifying the leader, and bureaucracy), leadership issues among augmentees (i.e., lack of belonging, lack of organizational support, lack of support from the home unit, lack of group cohesion, and issues related to promotion and recognition), leadership issues in multidisciplinary teams (i.e., proper training, team integration, culture, colour-centrism), leadership issues within units during deployments, leadership issues in reintegration, and effective leadership. Recommendations include the following: determining who actually are Air Force support personnel, as this would have implications for training; improving leadership from home units, as this would have implications for organization support for Air Force augmentee, reintegration issues, and recognition of Air Force members, and leadership training for leaders of multidisciplinary teams and training for Air Force members, especially Air Force augmentees, who will be working in multidisciplinary teams. Further recommendations from this research include improving overall leadership skills through training of all Air Force members, especially those in positions of leadership, for as the participants interviewed have suggested, holding a position of leadership is not necessarily an indicator of an effective leader.
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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 | 0.032 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".