First Do No Harm: Suggestions Regarding Respectful Autism Language
Notice bibliographique
Résumé
Nationally and internationally, efforts are ongoing to promote diversity, equity, and inclusion in healthcare and other fields. These efforts require consideration of ways in which language and assumptions impact individuals and communities. The autism and disability spheres are no exception. Indeed, the mental health of autistic people is predicted by the degree to which they feel society accepts them as autistic.1 Thus, we believe discourse that disparages autism could be harmful to autistic people’s well-being. Autistic individuals who face further stigma and discrimination due to other intersectional identities might be particularly vulnerable. Unfortunately, autism research and practice have traditionally used disparaging language grounded in the medical model.Some might object that alternatives to traditional medical model terms are subjective or unscientific. However, we believe traditional terminology is heavily laden with subjective value judgements. For example, the traditional term “disorder” has a decidedly negative connotation. It also implies that individuals’ own characteristics are responsible for their challenges, and it suggests a need to eliminate this disorder. In contrast, the more nuanced word “disability” allows both individual characteristics and societal or contextual barriers to contribute to challenges. The term disability thus appears to be both more scientifically appropriate and less stigmatizing toward a vulnerable population than disorder.In Table 1, we list various traditional terms and concepts that we believe are problematic, along with suggested replacements. We also suggest that practitioners and researchers balance a focus on autistic individuals' challenges with discussion of their strengths and potential. This balanced approach may be especially important for families of young children whose futures may be unclear and a source of considerable anxiety to caregivers.Furthermore, researchers and practitioners should be aware of an ongoing debate between supporters of identity-first (“autistic person”) and person-first (“person with autism”) language. Many autistic individuals support identity-first language2,3 and some fear that person-first language reflects negative attitudes toward autism.4 However, others endorse person-first language.2,3 The term “person on the autism spectrum” is often the most preferred term among autistic individuals and other stakeholder groups,2,3 and this verbiage is typically found to be acceptable by proponents of both person-first and identity-first language. Practitioners should ask about and respect the language preferences of individuals “on the spectrum” who can articulate their views.Overall, in light of concerns that typically-developing people struggle to understand autistic perspectives,5 we urge practitioners and researchers to strive to have empathy for how their language sounds to autistic people. We also suggest it can often be helpful to ask oneself if one would use similar phrasing with other marginalized communities. We feel that there needs to be a shift toward “cultural humility” and willingness to learn from autistic people about autistic identities and how to promote autistic well-being.Practitioners and researchers interested in a more detailed discussion of appropriate autism terminology should refer to Bottema-Beutel and colleagues.6 We provide definitions of neurodiversity terminology (eg, neurodiverse, neurodivergent) in Supplemental Table 2.
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 | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».