Decolonial Community Based Research in Psychology:Case Studies for Students and Educators
Notice bibliographique
Résumé
Decolonising involves centring the perspectives and knowledges of Indigenous and Global Majority communities. Participatory and community-based research methods can be decolonial when done properly, as they are grounded in building equitable partnerships with minoritised communities and valuing their lived experience and ways of knowing. Aligned with Indigenous principles, these approaches support the co-construction of knowledge that is reflective, contextual and rooted in relational accountability. This booklet presents five real examples of participatory and community-based research embedding decolonial reflections, primarily within health, psychology, and related fields. It is designed for students and educators and offers concrete, field-based examples grounded in researchers’ expertise and experiences. It focuses on strategies for designing and conducting research that is genuinely mutually beneficial and equitable. Case study 1 features Dr Nilu Ahmed’s exploration of the experiences and stories of Bangladeshi women living in the UK. Case study 2 highlights Dr Taylor-Jai McAlister’s experiences with suicide prevention research in and with Aboriginal communities in Australia. In case study 3, Catherine Jameson discusses Patient, Public and Community Involvement and Engagement (PCIE) in UK health research with ethnically diverse communities. Case study 4 presents Kacey Martin’s insights from a sexual health project with young Aboriginal people in Australia. Finally, case study 5 explores Dr Vera da Silva Sinha’s research on event-based time languages with Indigenous communities in the Brazilian Amazon. The booklet was organised and edited by Isabella Macedo de Lucas as part of her PhD project on decolonising research methods education in psychology. Her work is funded through a cotutelle PhD studentship between the University of Bristol and Macquarie University. Isabella’s supervisors are Associate Professor Peter Allen, Associate Professor Nilu Ahmed, and Professor Christopher Kent at the University of Bristol, as well as Professor Greg Downey and Dr Umut Ozguc at Macquarie University. The case studies were co-designed in collaboration with and co-edited by Dr Nilu Ahmed, Dr Taylor-Jai McAlister, Catherine Jameson, Kacey Martin, and Dr Vera da Silva Sinha. The artwork featured in this booklet is by Auá Mendes, an Indigenous artist from the Mura people of Brazil. Auá is a graphic artist, illustrator, muralist, and art educator born in Manaus (1999) and based in São Paulo since 2020. She holds a degree in graphic design, and her career combines her cultural identity with visual productions that engage with contemporary themes. Her work includes impactful urban interventions (murals up to 60 meters) and participation in projects and campaigns addressing issues such as female empowerment, diversity, and the appreciation of the Amazon. Auá Mendes is recognised as a significant voice in contemporary Brazilian art, and her work has been exhibited internationally. Connect with Auá on Instagram @aua___art.
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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 | 0,032 | 0,022 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,020 | 0,019 |
| Communication savante | 0,009 | 0,009 |
| Science ouverte | 0,005 | 0,016 |
| Intégrité de la recherche | 0,007 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».