Army, Navy, Air Force and Research? The Vocation of Scholarship as an Applied Discipline in the Canadian Forces
Bibliographic record
Abstract
This article is a personal and professional reflection on scholarship and research as applied to a very large and mechanistic organization – the Canadian Forces. A specialist cadre of officers within the Canadian Forces is dedicated to the applied discipline of Training Development. Training Development is the practical application of adult education theory and, in an academic institution, would normally provide ample scope for research. However, the shortage of professional Training Development Officers in the Canadian Forces leaves little time for research given the urgent requirement to train and deploy ever-increasing numbers of Army, Navy and Air Force personnel to theatres of operations abroad. Those officers who practice scholarship through research pursuits often do so to satisfy personal rather than professional goals. The engagement in professional research projects is filled with challenges that include identification of key stakeholders, selection of a topic, and the ethics of rationalizing personal areas of academic interest with military areas of need. The result is a focus on applied rather than academic research. To ethically conduct applied research using Canadian Forces subjects requires the active participation of unrelated departments and the use of both personal and work time to complete the research task. The greatest gains in efficiency can be achieved through position related research. Although there are challenges associated with the pursuit of scholarship in a military setting, there is also ample scope for examination of topic areas not previously addressed through research. The article concludes with recommendations for research into institutional effectiveness, leader experiences and future requirements through a combination of position related and personal interest generated research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.049 | 0.050 |
| Scholarly communication | 0.028 | 0.011 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".