Evidence map›Paper›PMID 42533940›Full record

ReviewJournal of military, veteran and family health2025

Diversifying theory and models for change: Why multiple frameworks better advance equity and belonging in the Canadian Armed Forces.

Vanessa Brown

Abstract readReview
In one paragraph

Review in Journal of military, veteran and family health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Vanessa BrownDepartment of Defence Studies, Canadian Forces College, Toronto, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Critical theory as well as formal analytic models and tools across gender, sociological, and intersectional studies provide insight as to why generic culture change initiatives have not led to desired outcomes in the Department of National Defence (DND) and Canadian Armed Forces (CAF). Diversifying theories and models for culture change and applying these separately for DND and CAF may better increase cultural changes intended to advance equity and belonging. Methods: A review of critical theory is used to illustrate how social constructions of power relate to inequity across institutions, including the military. Moreover, institutional and social identity theory are presented to identify substantive differences between DND and CAF. An application of Richard Scott's method of institutional analysis highlights distinct organizational functions of DND and CAF, while the use of gender-based analysis plus identifies diversity in treatment and experience related to social hierarchies maintained uniquely within each organization. Finally, an analysis of knowledge transfer, legitimacy, power, and urgency of diverse groups illuminates historic social constructions of power, setting the conditions for contemporary inequities. Results: Findings illustrate that a one-size-fits-all approach to culture change across the wider Defence Team may avoid necessary thinking about institutional distinctions. Discussion: To fully comprehend inequities experienced by DND personnel and CAF members, each institution requires separate but comparative approaches to change. These benefit from applications of critical theory, as well as diversified analysis models and tools to address localized social constructions of power and inequity.

Indexed as

CAFculture changedefenceDNDequityGBA+GBA Plusinstitutional analysisintersectionalitymilitary

Identifiers

PMID42533940
PMCPMC13293143

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.