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Record W4402186156 · doi:10.1521/jsyt.2024.43.1.5

Stories of Skills and Values: What Therapists Can Learn From Autistic Young People in Mumbai, India

2024· article· en· W4402186156 on OpenAlexaffvenue
Jill Sanghvi, D. Donald Sawatzky

Bibliographic record

VenueJournal of Systemic Therapies · 2024
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Research on autism in the past two decades has primarily focused on medical characteristics and psychological consequences. What remains largely undocumented are the lived experiences of autistic young people. The current study explores the skills and values of autistic young people in the Indian context from the first-person perspective. The inquiry was guided by narrative inquiry and dialogical narrative analysis, embedded in the social constructionist framework. Six autistic young people, between 10 and 18 years old, were interviewed; analysis of the results brought forth four commonalities of skills and values: (1) diverse understandings of autism; (2) understanding social situations, their own needs, and others’ responses; (3) thinking outside the box; and (4) helping and caring for others. Rather than having a diagnosis of autism labeled as a deficit, these findings open up possibilities for therapy work to look different by supporting people to hold on to their identity as autistic people.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score0.570

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.291
Teacher spread0.275 · 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 teacher head, 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

Citations2
Published2024
Admission routes2
Has abstractyes

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