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Record W7115039206

In their words: Understanding social motivation in Autistic adults

2025· dissertation· en· W7115039206 on OpenAlexaff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2025
Typedissertation
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsSocial relationAutismQualitative researchSocial isolationPerception
DOInot available

Abstract

fetched live from OpenAlex

Traditionally, Autism research has been dictated by a neurotypical understanding and theorization of normality and functioning, following the medical model of disability. This model views Autistics, who function differently from non-autistics, as inherently abnormal or inadequate (Olkin, 1999; Retief & Letšosa, 2018). The way researchers have conceptual-ized Autistic Social Motivation (SM), or the mechanisms that drive individuals to orient to and participate in the social world, reflects this view. Based on findings from studies in which Autistics manifested fewer (neurotypical) SM behaviors (social orienting, seeking and liking, and social maintaining) than their neurotypical peers, Chevalier et al. (2012) con-cluded that Autistics have reduced SM compared to neurotypicals. Bottini (2018), following her systematic review of studies on social reward processes in Autistics, argued that SM might manifest differently in Autistics, but that it is still present. Jaswal and Akhtar (2018) further argued that neurotypical indicators of SM may not be suitable indicators of SM in Autistics. Instead, they offered explanations unrelated to SM that prevent Autistics’ SM from manifesting in expected ways. Due, for example, to eye gaze avoidance resulting from processing overload. The accounts of some Autistics illustrate that they do seek to engage with the social world: “The way people see autistic folks is that they don't want to be around other people. That’s wrong. The truth about autistic people is that we want what everyone else wants, but we are sometimes misguided and don't know how to connect with other peo-ple.” (Suskind, 2014, p. 366 in Jaswal & Akhtar, 2018).No research has, to my knowledge, explicitly asked how Autistic adults, of any gen-der, would characterize their SM. To do so, I, an Autistic autism researcher, interviewed Autistics about their social motivation and the meanings assigned to their social experiences. Specifically, how they think, feel, and behave in relation to their SM. The Interview Proto-col was organized around eight a priori SM themes (Social Opportunities, Social Interest, Meaning of Relationships, Value of Social Support, Perception of Self in the Social World, Social Initiative Taking, Social Flexibility, and Motivation to Conform Socially) that were elaborated based on a review of measures on SM and social functioning in typical, Autistic, and other clinical populations (Constantino & Gruber, 2012; Elias & White, 2020; Gong et al., 2018; Hurley et al., 2006; Leary et al., 2013; Llerena et al., 2013; Phillips et al., 2019; Raine, 1991; Richard & Schneider, 2005; Yager & Iarocci, 2013). The Protocol was also informed by feedback from four participants (Castillo-Montoya, 2016). A total of 12 Autistic adults without Intellectual Disabilities living in Canada were interviewed, in French or Eng-lish, virtually or in person. On average, interviews lasted 1.5 hours. Following Braun and Clarke's (2006) Reflexive Thematic Analysis guidelines, we developed nine themes sur-rounding the factors contributing to and hindering SM in our sample of Autistic adults. These findings provide a novel, lived-experience-informed understanding of SM in Autis-tics, making the Interview Protocol a resource for Autistic self-understanding and a tool to be used and improved by researchers. Additionally, these insights offer others knowledge into engaging Autistics in more motivating and affirming ways

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0040.008
Open science0.0010.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.057
GPT teacher head0.297
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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