Notice bibliographique
Résumé
Background/Context: Unconscious racial bias (URB) can be a pernicious form of racism. In light of increased awareness of and research on the subject, URB work has become a key focus of equity work in health care, education, and corporate contexts as part of broader calls for racial justice. In Canada, targeting URB in education has become a policy priority at the national, provincial, and school board levels. The role of individual and organizational URB is now widely recognized in policy as central to equitable outcomes in schooling; however, research is limited on how to engage these forms of racism in educational contexts. Prevailing approaches to URB work in schools often include truncated one-off workshops, which leave unaddressed the connections between the individual racial biases, and the operations of white supremacy and racism at the institutional, systemic, and structural levels. Purpose/Objective/Research Question/Focus of Study: While URB is increasingly well-understood by social psychologists, there has been limited engagement from critical scholars working in areas such as critical race theory (CRT), anti-colonialism, and critical whiteness studies—despite the popularity of interrogating URB as an anti-racism strategy in education. CRT in education has laid bare and problematized the central function of schooling in the safeguarding and management of white supremacy. This project emerged from a dual recognition of URB as a productive entry point for racial awareness and anti-racism work, alongside a significant concern about the failure of mainstream URB discourse to address structural racism and white supremacy—masking at times the deeper ways that Euro-colonial racism underpins social relations in contemporary U.S., Canadian, European, and other contexts. This work seeks to address these limitations in the design of the study through deep work with participants. Specifically, the study sought to understand better the impacts of reading critical texts focusing on systemic, structural, and institutional racism on teachers’ understandings of their own racial biases, as well as teachers’ perspectives on the impacts of reading critical texts in terms of their professional practices. Research Design: This article reports on the findings of a 10-month study with secondary teachers in Toronto, Canada, focusing on critical approaches to racial bias mitigation in education. In addition to asking participants to enact a series of URB mitigation strategies developed in the field of social psychology, this study also required participants to read and reflect on one of the following critical anti-racism nonfiction texts: White Fragility: Why It’s So Hard for White People to Talk About Racism by Robin DiAngelo (2018); Policing Black Lives: State Violence in Canada From Slavery to the Present by Robyn Maynard (2017); Everyday Antiracism: Getting Real About Race in School, edited by Mica Pollock (2008); Unsettling the Settler Within: Indian Residential Schools, Truth Telling, and Reconciliation in Canada by Paulette Regan (2014); and Monstrous Intimacies: Making Post-Slavery Subjects by Christina Sharpe (2010). The project was designed using multiple data sources from participants, including electronic survey responses, ongoing journaling/reflection, a midpoint check-in questionnaire, and a final interview. These multiple entry points, as well as the duration of the project, aimed to go beyond the taken-for-granted and toward deeper understanding over time. Conclusions/Recommendations: Findings suggest that reading these works impacted teachers’ understandings of race and racism in terms of their teaching, as well as in terms of their personal relationships to race and racism, increasing their inclination and ability to address race and anti-racism. This work allowed for critical reflection to seep into the most intimate and invisible moments of operationalized whiteness in the professional and personal spheres of participants. This suggests an important complementarity between teacher intervention practices emerging from social psychology, and the introduction and engagement of critical anti-racist and anti-colonial texts in terms of teachers’ work for racial justice.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
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 tête enseignante, 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 ».