Critiquing unearned military privilege: unpacking the invisible duffle bag
Bibliographic record
Abstract
This Encounters article explores how unearned privilege in the Canadian Armed Forces (CAF) is structured, how it operates to privilege certain personnel over others with negative implications for the health and well-being of those who are marginalized, and how it can be changed to the benefit of CAF personnel and the organization as a whole, as well as Canadian society. The article adapts Peggy McIntosh’s ‘White privilege: Unpacking the invisible knapsack’ to a military context, to unpack the ways in which everyday military privilege operates in the CAF, like an invisible duffle bag of military norms, policies, power relations, practices, traditions, and training. The checklist can be used to begin, continue, and enhance conversations about military culture change by exploring how individual privilege is connected to and enabled by structural power relations. The article concludes with a discussion of the importance of understanding how military privilege intersects with societal privilege, with concomitant implications for both contexts.
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 | 0.025 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.032 | 0.125 |
| Scholarly communication | 0.019 | 0.020 |
| Open science | 0.004 | 0.017 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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".