Bibliographic record
Abstract
Offering a Canadian perspective on the emotional health of servicemen and women, Military Operations and the Mind brings together researchers and practitioners from across the country to consider the impact that ethical issues have on the well-being of those who serve. Stemming from an initiative to enhance the lives of serving members by providing them with the best education and training in military ethics before and after deployments, this volume will better inform politics and public policies and enhance the welfare of the soldiers, sailors, and airmen and women who serve in singular, often harsh, and sometimes dangerous conditions. By integrating into the analysis the critical issue of well-being, this emerging field demonstrates a more holistic approach and is distinct from other fields in military, historical, philosophical, and behavioural studies. The first study of its kind, Military Operations and the Mind presents a new and helpful way to focus on the life of soldiers not only in operations overseas, but also once they return home. Contributors include Peter Bradley (Royal Military College of Canada), Victor M. Catano (Saint Mary’s University), Danielle Charbonneau (Royal Military College of Canada), Howard Coomb (Royal Military College of Canada), Karen D. Davis (Defence Research and Development Canada), Colonel Richard Dickson (Canadian Army Land Warfare Centre), Joe Doty (Duke University), Allan English (Queen's University), Peter Gizewski (Department of National Defence), Heather Hrychuk (Centre for Operational Research and Analysis), E Kevin Kjelloway (Saint Mary’s University), Allister MacIntyre (Royal Military College of Canada), Deanna Messervey (Queen’s University), Damian O'Keefe (Saint Mary’s University), Brigadier General (Ret’ed) G. E. Sharpe, Shaun Tymchuk (retired Canadian infantry officer), SLt Ethan Whitehead (Royal Canadian Navy), and Daphne Xu (National Institute of Education, Singapore).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.016 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".