Re-Visioning Counsellor Education: Centring Justice, Accessibility, Inclusion, Diversity, and Equity
Notice bibliographique
Résumé
In this chapter Sandra and Melissa focus on justice-doing within counsellor education. They highlight the necessity of learning environments and institutional cultures characterized by JAIDE (i.e., justice, accessibility , inclusion, diversity, and equity), in which all learners can thrive. They pair this with integration of cultural responsivity and social justice (CRSJ) practices into every facet of curricula and field placements to ensure that students are prepared to challenge systemic inequities and foster micro-, meso-, and macolevel change. They note the responsibility of educators and institutions to fully address the “Calls to Action” of the Truth and Reconciliation Commission of Canada. They organize the chapter into the following themes: (a) shifting from learning about to learning with and from, which includes embracing multiple ways of knowing, doing, and being; (b) implementing anti-oppressive and decolonial pedagogies to enhance the cultural meaningfulness of pedagogy; (c) creating safer, more inclusive learning spaces; (d) faculty development, which includes continued learning and unlearning through self-reflective processes; (e) program-level integration of CRSJ practices to ensure pluralism in views of health and healing are equitably reflected in all aspects of counsellor education; and (f) institutional advocacy to address access barriers and increase representation of racialized and other marginalized groups among faculty, staff, and learners. An invitation to action invites all members of the academic community to embrace the scholar–practitioner–advocate–leader model. Melissa and Sandra appreciate the insights about counsellor education offered by these co-authors: • Jane Arscott draws on her many years of experience of advocating for accessibility of education and recognition of learning derived from nonconventional and undervalued contexts and sources to re-vision education and learning. • Kim Ashbourne encourages counsellor educators to think beyond academic accommodation and embrace transformative digital accessibility in their teaching praxis. She suggests five high leverage changes educators can make. • Jagdeep Kundi reflects on her experience of mentorship as a student-led journey of learning and unlearning through which she was able to embrace decolonization and Indigenous ways of knowing. • Ya Xi (Nancy) Lei, Sherani Sivakumar, and Gina Wong speak to building a sense of safety in community as students and faculty engaged in the Asian Mental Health: Research, Advocacy, Working (AMH: RAW) group. • Ya Xi (Nancy) Lei offers insights into racialized students’ well-being through her research on critical incidents in racial (in)equity in Canadian counsellor education. • Marguerite Lengyell shares a series of videos that bring to life her counsellor education experiences, offering concrete strategies for navigating the complexities of CRSJ work in practice.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,010 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,015 | 0,028 |
| Communication savante | 0,021 | 0,015 |
| Science ouverte | 0,002 | 0,013 |
| Intégrité de la recherche | 0,006 | 0,020 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».