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Enregistrement W4392681530 · doi:10.22318/icls2023.360863

“When We’re in Spaces Among People of Colour, Your Ideas Just Flow”: Politicized Trust and Educational Intimacy in Activist Spaces

2023· article· en· W4392681530 sur OpenAlexaff
Joe Curnow

Notice bibliographique

RevueProceedings. · 2023
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueInnovative Education and Learning Practices
Établissements canadiensUniversity of Manitoba
Organismes subventionnairesnon disponible
Mots-clésSociologySolidarityDebriefingGrievancePoliticsCollective identityIdentity (music)Social psychologyMedia studiesEpistemologyAestheticsPsychologyPolitical scienceLaw

Résumé

récupéré en direct d'OpenAlex

This paper examines how relationships of educational intimacy and politicized trust were constructed in an activist community.Bridging theories of politicization and activist becoming with emerging research on the significance of relationships for identity development and solidarity, this paper brings micro-interactional data of how relationships are constructed and why they matter.Tracing a group debrief by members of colour within the Fossil Free UofT activist group allows us to see how humour constructed intimacy alongside intense disclosure and collectivized grievance construction.This contributes to work in the learning sciences to demonstrate the political contexts and consequences of learning and provides tools for activists to organize learning ecologies for educational intimacy and politicized trust. On relationships and learningThe question of how relationships shape learning has animated many of us in the learning sciences over the last decades, and particularly in recent years as attention in our field has shifted to attend more closely to the political and ethical dimensions of learning.Recent research has examined how relations of educational intimacy (Uttamchandani, 2021) and politicized trust (McKinney de Royston & Vakil, 2019) have made specific forms of learning possible, and this work, alongside other interventions toward understanding relationships and politicization is vital in understanding how other possible futures are imagined and enacted through the joint work of community members.This paper theorizes political transformation through a sociocultural lens, arguing that politicization is a learning process, one that unfolds not in the minds of individual participants, but rather as coconstituting processes of development involving the political concepts, practices, epistemologies, and identities of learners as they transform through their engagement in building new possible futures (Curnow, et al., 2020).These theoretical and analytical questions align closely with questions emerging from social movements, where the need to understand how, when, and why some relationships support learning and collective action to change social systems toward more just futures (and why some do not).This question was a persistent undercurrent in the work of FossilFree UofT, a campus-based climate activist group.In their campaign to push the University of Toronto to divest the endowment funds from the 200 fossil fuel companies with the largest reserves, many of the young people engaged in this work dramatically shifted their political orientations.So often, young activists in the campaign wondered why some people "wouldn't learn" and why, by contrast, other spaces felt so nurturing of their political engagement and growth as climate justice activists.In this paper, I take up those questions, asking how relationships of educational intimacy enabled politicization.I use one particularly rich interaction as the basis of analysis, looking at video of an impromptu debrief of people of colour after a tense meeting.In this debrief, we can hear explicit talk about the value of relationships of trust and shared experience, and also see the ongoing unfolding of educational intimacy.Building from Uttamchandani (2021) and Vakil & McKinney de Royston (2019), I argue that the relationships of intimacy and politicized trust enabled participants in the debrief to become politicized, and that the politicization process further entrenched and reinforced their relationships.To make this argument, I begin with a brief overview of recent research on relationships, politics, and learning from sociocultural perspectives.I then provide more detail on the context of Fossil Free UofT before describing the participatory action research project we undertook, the data collection, and the methods of analysis.I then pivot to an analysis of the debrief, highlighting the sensemaking happening in real time, and identifying how the relationships of politicized trust and intimacy make that learning possible. Literature: Relationships, politics, and learning in the learning sciencesResearch that interrogates learning as a sociocultural and interactional accomplishment is foundational to the learning sciences.Within that broad framing, we can look more specifically at work that attends to the affordances for learning that relationships enable.There has been work investigating how friendship shapes learning processes and outcomes among students (Takeuchi, 2016;Jackson, et al.;2020;Vakil & McKinney de Royston, 2019), among social movement organizers (Curnow, et al., 2021;Teeters & Jurow, 2018;Uttamchandani, 2021; Vea, 2018), between teachers and students (Boaler, 2008;McKinney de Royston, et al., 2017), between research collaborators (Vakil, et al., 2016), and among researchers (Jackson, et al., 2020).All of this work recognizes that learning is social, and that who learners are surrounded with matters for what they learn, how they learn, and how

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 machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,010
Version: metacan-v3-hybrid-931329e0061cStatut 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 enseignants0,011
Score d'incertitude au seuil0,022

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,010
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0110,028
Communication savante0,0080,007
Science ouverte0,0010,007
Intégrité de la recherche0,0020,004
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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 GPT0,404
Écart entre enseignants0,333 · 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 source (Gemma direct ou Codex distillé), 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'admission1
Résumé présentoui

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