« Je suis humain, tout comme vous » : ce que les expériences vécues intersectionnelles et neurodivergentes apportent à la recherche sur l'accessibilité

Titre original en anglais : "I Am Human, Just Like You": What Intersectional, Neurodivergent Lived Experiences Bring to Accessibility Research

Cette publication est incluse dans le projet « Contributions académiques de personnes autistes sur l’autisme ». un auteur·ice de cette publication est identifié·e comme autiste dans le projet.

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Le, L. (2024). "I Am Human, Just Like You": What Intersectional, Neurodivergent Lived Experiences Bring to Accessibility Research. The 26th International ACM SIGACCESS Conference on Computers and Accessibility, 1-20. https://doi.org/10.1145/3663548.3675651

Date de publication: 20/10/2024 Ajout dans AutiHub: 21/10/2026 Type: Autre Langue de l’article: Anglais
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Auteurs

Auteur·ices des publications
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1 / 1 (100,0 %)
  1. Lindy Le *

Résumé

La prévalence croissante de la neurodivergence a conduit la société à reconnaître davantage l'importance de la neurodiversité. Pourtant, les perceptions sociétales de la neurodivergence demeurent majoritairement négatives. S'appuyant sur les études critiques du handicap, les chercheurs en accessibilité ont montré comment les présupposés neuronormatifs dominent l'IHC. Malgré leurs orientations, les personnes neurodivergentes et handicapées restent marginalisées dans la recherche sur les technologies. En particulier, les identités intersectionnelles restent largement absentes de la recherche sur la neurodivergence en IHC. Dans cet article, je partage ma perspective en tant que personne extérieure à la communauté de la recherche universitaire : j'utilise l'autoethnographie critique pour analyser mes expériences de compréhension, d'acceptation et de valorisation de ma neurodivergence au sein de systèmes de pouvoir, de privilège et d'oppression. En utilisant Data Feminism comme guide accessible et pratique de l'intersectionnalité, je dégage trois principes pour reconceptualiser la neurodivergence afin de mieux inclure les expériences intersectionnelles : (1) la neurodivergence est une différence fonctionnelle, et non un déficit ; (2) le handicap neurodivergent est un moment de friction, et non une étiquette statique ; et (3) l'accessibilité de la neurodivergence est une pratique collaborative, et non une solution unilatérale. J'examine ensuite ces principes dans le contexte des recherches existantes en IHC, en appliquant la même perspective intersectionnelle. Enfin, je propose trois suggestions sur la manière dont la recherche sur l'accessibilité peut appliquer ces principes dans de futurs travaux, afin de combler l'écart entre la théorie et la pratique de l'accessibilité dans la recherche sur la neurodivergence en IHC.

The increasing prevalence of neurodivergence has led society to give greater recognition to the importance of neurodiversity. Yet societal perceptions of neurodivergence continue to be predominantly negative. Drawing on Critical Disability Studies, accessibility researchers have demonstrated how neuronormative assumptions dominate HCI. Despite their guidance, neurodivergent and disabled individuals are still marginalized in technology research. In particular, intersectional identities remain largely absent from HCI neurodivergence research. In this paper, I share my perspective as an outsider of the academic research community: I use critical autoethnography to analyze my experiences of coming to understand, accept, and value my neurodivergence within systems of power, privilege, and oppression. Using Data Feminism as an accessible and practical guide to intersectionality, I derive three tenets for reconceptualizing neurodivergence to be more inclusive of intersectional experiences: (1) neurodivergence is a functional difference, not a deficit; (2) neurodivergent disability is a moment of friction, not a static label; and (3) neurodivergence accessibility is a collaborative practice, not a one-sided solution. Then, I discuss the tenets in the context of existing HCI research, applying the same intersectional lens. Finally, I offer three suggestions for how accessibility research can apply these tenets in future work, to bridge the gap between accessibility theory and practice in HCI neurodivergence research.

Bibliographie citée par cette référence

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Vue d’ensemble de la bibliographie citée

Ces indicateurs décrivent la bibliographie citée par cette publication. Un nom d’auteurice est compté chaque fois qu’il apparaît dans une référence citée : une même personne peut donc être comptée plusieurs fois. Les noms qui ne sont pas encore associés à un·e auteurice déjà présent·e dans AutiHub sont traités comme inconnus, pas comme non autistes. Dernier calcul : 27/10/2026 10:35.

Références citées
259
Avec un DOI
137
Sans DOI, à partir du texte brut de la bibliographie
121
39 / 259 (15,1 %) références citées comprennent au moins une personne identifiée comme autiste.
Références avec données à compléter
53 / 259 (20,5 %)
Références avec noms d’auteurices détectés
214 / 259 (82,6 %)
Sans nom d’auteurice détecté
45
Sans titre structuré
51
Sans identifiant stable
119
Références avec noms bruts d’auteurices restant à vérifier
44
Références avec problème de récupération des métadonnées externes
0
Ces indicateurs portent sur les références citées affichées sur cette page, après fusion des doublons techniques. Une référence sans DOI peut quand même soutenir les statistiques d’auteurices lorsqu’un titre et des noms d’auteurices sont disponibles.
Noms d’auteurices détectés dans la bibliographie citée
567
À partir du DOI ou de métadonnées externes
559
À partir du texte brut validé de la bibliographie
8
Noms bruts déjà validés
8
Noms bruts restant à vérifier
44
185 / 567 (32,6 %) noms sont associés à un·e auteurice déjà présent·e dans AutiHub. 382 / 567 (67,4 %) noms ne sont pas encore associés.
Noms associés à une personne identifiée comme autiste
47 / 567 (8,3 %)
Calculé sur l’ensemble des noms d’auteurices détectés dans la bibliographie citée. Parmi les noms associés à un·e auteurice déjà présent·e dans AutiHub : 47 / 185 (25,4 %). Personnes distinctes identifiées comme autistes : 28 / 490 (5,7 %).
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