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Enregistrement W4390942661 · doi:10.5334/ijic.icic23611

Community Engagement from Theory to Practice: Co-design and Implementation of Inclusive Language Principles in a Community-based Organization Serving People with Disabilities

2023· article· en· W4390942661 sur OpenAlexaffabout
Joseph Fulton, Alana Armas, Hayley R. Crooks, Gift Tshuma, Karen Whitehead-Lye, W. Francis Fung, Rambel Palsis, T. H. Trang Nguyen, Sasha Elford, Barbara Moore, Michelle Nelson

Notice bibliographique

RevueInternational Journal of Integrated Care · 2023
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueEducation and Teacher Training
Établissements canadiensUniversity of TorontoUniversity of ManitobaSinai Health SystemMarch of Dimes Canada
Organismes subventionnairesnon disponible
Mots-clésCommunity engagementPlain languagePublic relationsPraxisSociologyPolitical science

Résumé

récupéré en direct d'OpenAlex

Introduction: March of Dimes Canada (MODC) is one of the largest non-profit organizations in Canada that provides programs and support services to people with disabilities. MODC is in the process of transforming all its programming and services using co-design to better meet the needs of people with disabilities. The Empowering Client Voices (ECV) initiative was designed to create a co-designed community engagement framework to center the voices and ideas of people with disabilities in how the organization engages with its community and provides services. This project looks to fill a gap in knowledge of how community-based organizations can move from theory to praxis when using co-design and community engagement. Methods: The initiative is a three-phase process: (1) internal review of current organization engagement practices; (2) external environmental scan and a rapid review; and (3) two advisory committees to develop the principles for greater community engagement. The purpose of the co-designed community engagement framework is to create actionable principles based on the guidance of our advisory committees and other research tools. Phases 1 and 2 will create foundational themes to be discussed with our advisory committee made of people with disabilities. These themes will help provide initial guideposts for discussions about what community engagement should be within MODC. Language will be the first theme to be explored with the advisory committee to create recommendations and guidelines for better communication and inclusive language across the organization. Results: The inclusive language recommendations and guidelines developed by the ECV Advisory Committee will initiate the development of an inclusive language toolkit by the research team. The inclusive language toolkit will be shared throughout the organization as a template to follow when discussing disability and people with disabilities using language that represents our community in their own words. Before the start of the ECV Initiative, inclusive language guidelines did not exist within the organization requiring the development and implementation of a change-management process at the Micro (MODC staff members) and Meso (Organization) to ensure the guidelines will be adopted across a national community-based organization. Discussion and Conclusion: This poster presentation will outline the development of the co-designed inclusive language toolkit and change management process for our organization to adopt standardized inclusive language through all forms of community engagement and communication in collaboration with people with disabilities in our communities of operation. International audiences can use our project as a case study of how co-design can inform and drive organizational change. This case study will highlight the implementation factors that were found to be advantageous in a community-based organization, factors that hindered organizational change, and mitigation techniques used to make lasting change across the organization. Lessons and Future Research: Future research for the ECV Initiative will continue to implement the additional themes within the ECV community engagement framework with the intention of making the additional toolkits based on co-designed themes and change management knowledge products publicly available to help other community-based organizations improve their own community-engagement practices.

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)0,003
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
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 enseignants0,088
Score d'incertitude au seuil0,995

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
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 Opus0,060
Tête enseignante GPT0,419
Écart entre enseignants0,358 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
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

Citations0
Publié2023
Routes d'admission2
Résumé présentoui

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