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Record W2754922100 · doi:10.1177/1362361317702561

A qualitative study of the service experiences of women with autism spectrum disorder

2017· article· en· W2754922100 on OpenAlexafffund
Ami Tint, Jonathan A. Weiss

Bibliographic record

VenueAutism · 2017
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsYork University
FundersNational Institute of Child Health and Human DevelopmentNational Institute of Mental HealthCanadian Institutes of Health ResearchPennsylvania Department of HealthRobert Wood Johnson Foundation
KeywordsPsychologyAutismAutism spectrum disorderQualitative researchDevelopmental psychologyClinical psychologySociology

Abstract

fetched live from OpenAlex

It is recognized that the experiences of women with autism spectrum disorder are often underrepresented in the literature. In this study, 20 women with autism spectrum disorder participated in five focus groups with discussions centered on their service use, unmet service needs, and barriers to care. Overall, women emphasized high unmet service needs, particularly with respect to mental health concerns, residential supports, and vocational and employment services. Participants also perceived many service providers as disregarding or misunderstanding women's service needs. Findings of the current exploratory study are discussed in relation to areas of future research required to ensure effective care for this understudied population.

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)0.009
metaresearch head score (Gemma)0.013
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: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0120.008
Scholarly communication0.0030.004
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.057
GPT teacher head0.416
Teacher spread0.359 · 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

Citations148
Published2017
Admission routes2
Has abstractyes

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