Diversifying theory and models for change: Why multiple frameworks better advance equity and belonging in the Canadian Armed Forces
Bibliographic record
Abstract
LAY SUMMARY This article examines shortcomings of culture change initiatives within the Department of National Defence (DND) and Canadian Armed Forces (CAF). It argues that current one-size-fits-all approaches fail to address unique cultural dynamics in each institution. Using critical theory and various analytic models, the article highlights how social constructions of power contribute to persistent inequities in military and defence environments. By exploring militarized masculinities and intersectional, institutional, and social identity theories, it demonstrates differences between DND and CAF that need to be considered in culture change strategies. Additionally, analytic models such as Richard Scott’s institutional analysis reveal distinct organizational functions shaping everyday interactions within each entity, just as applications of the gender-based analysis plus (GBA Plus) tool uncovers inequitable experiences based on unique social hierarchies of DND versus CAF. Thus, effective culture change requires tailored approaches that recognize distinctions within DND and CAF. The article argues that to foster equity and belonging, diverse theoretical frameworks and tools are needed to address specific challenges faced by DND members and CAF personnel. A deeper understanding of these localized issues is essential for achieving desired cultural transformations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".