Canadian Military Chaplains: Bridging the Gap Between Alienation and Operational Effectiveness in a Pluralistic and Multicultural Context
Bibliographic record
Abstract
Canadian Forces' chaplains are able to negotiate the disparities between institutional goals and the human needs of military personnel through their ‘ministry of presence’, capacity to operate outside the chain of command, and symbolically ‘neutral’ rank, to provide meaningful support and pastoral care. This article uses sociological and phenomenological perspectives based on interviews with Christian military chaplains in the Canadian Forces as well as other studies on religion in Canada and religion in late modernity to examine the changing face of religion in Canada, provide an overview of the development of the Canadian Forces' Chaplain Branch, discuss new forms of religious diversity, and finally, examine how Canadian military chaplains today continue to contribute meaningfully to military operations in their ongoing support of human needs. This analysis offers insights into the alienation that can come from working in a modern bureaucratic institution, the challenges of adapting to a religiously diverse environment, and the difficulty of bridging the gap between these two spheres in order to sustain operational effectiveness.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.058 | 0.027 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".