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Enregistrement W4206456041 · doi:10.22215/etd/2021-14630

Integrating gender and cultural perspectives in Canada’s Professional Military Education: transforming military culture through informed leadership

2021· dissertation· en· W4206456041 sur OpenAlexafffundabout
Vanessa Brown

Notice bibliographique

Revuenon disponible
Typedissertation
Langueen
DomaineSocial Sciences
ThématiqueGender, Security, and Conflict
Établissements canadiensCarleton University
Organismes subventionnairesCanadian Armed Forces
Mots-clésSocializationInclusion (mineral)CurriculumContext (archaeology)PedagogySociologyPolitical scienceIdentity (music)Transformational leadershipPublic relationsGender studiesSocial science

Résumé

récupéré en direct d'OpenAlex

This dissertation investigates and invests in the possibility for feminist transformational change within militaries as well as the potential for militaries to be 'forces for good.' The research considers whether militaries can contribute to feminist progress and work towards the cultural inclusion of diverse members within militaries due to personnel's exposure to gender and cultural perspectives within Professional Military Education. The project narrows its investigation to the mid-to-senior graduate level education of Canadian military officers within the Joint Command and Staff Programme at Canadian Forces College. It applies post-modern feminist, intersectional and militarized masculinities theories to understand the military learning environment and to analyze the inclusion and reception of critical theory by military learners. The research draws on contemporary pedagogic literature to make recommendations for optimizing learning environments and professional competencies to facilitate inclusive security and organizational culture change. Acknowledging the context of dominant masculinist and white centering constructions of military identity and socialization, this investigation asks: To what extent are gender and cultural perspectives integrated into mid-to-senior level Canadian Professional Military Education? If and in what ways military socialization and culture shapes the learning environment and the reception of this education? Finally, if and in what ways such learning has facilitated feminist transformations in the military and beyond? The research draws from a feminist critical discourse analysis of six semi-structured focus groups across military and civilian educators, curriculum developers, librarians, and students as well as eight in-depth interviews with military students before graduation and eight follow-up in-depth iii interviews with military graduates after at least three months in command and/or staff positions. The study's sociological ethnographic approach illuminates discursive as well as lived experiences with teaching and learning across staff and students. Findings of the research ultimately highlight that while limited, exposure to gender and cultural perspectives, including critical feminist and anti-racist theories and frameworks has had positive professional effects. Graduate respondents report being better able to think critically about security, operations, institutional policy, and leadership, as well as institutional systems, structures, and culture. Some report being empowered by these concepts to facilitate inclusive security domestically and abroad and to advance organizational culture change. For Papa. I'll be loving you always. I wrote this dissertation in my home office in Toronto, situated on the traditional territory of many Indigenous nations including the Mississaugas of the Credit, the Anishnabeg, the Chippewa, the Haudenosaunee and the Wendat peoples. My place of work and residence falls under Treaty 13 referred to as the Toronto Purchase negotiated between the Mississaugas of the Credit and the Crown. Indigenous peoples of this land are its longstanding guardians. As a person of settler colonial heritage, I benefit from the land, its communities of people, and their knowledge. I acknowledge these privileges and am committed to supporting the ongoing stewardship of Turtle Island and Toronto by diverse First Nations, Inuit, and Metis peoples.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,414
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,071
Tête enseignante GPT0,354
Écart entre enseignants0,283 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations6
Publié2021
Routes d'admission3
Résumé présentoui

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