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Record W4220761613 · doi:10.1177/00084174221085433

Exploring Autism, Culture, and Immigrant Experiences: Lessons from Sri Lankan Tamil Mothers

2022· article· en· W4220761613 on OpenAlexvenueaboutno aff
Kajaani Shanmugarajah, Peter Rosenbaum, Briano Di Rezze

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2022
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsnot available
Fundersnot available
KeywordsTamilImmigrationPsychological interventionQualitative researchOccupational therapyMedicineCultural competencePsychologyDescriptive researchNursingPsychiatrySociologyPolitical sciencePedagogySocial science

Abstract

fetched live from OpenAlex

Background: Canada is home to a mosaic of cultures with immigrant communities from a wide range of countries, but there are significant variations in how autism spectrum disorder (ASD) may be understood across different immigrant groups, including Sri Lankan Tamils. Such gaps in knowledge may present challenges for immigrant families that are trying to access appropriate care for their child, including occupational therapy services. Purpose: This descriptive qualitative study aimed to better understand the experiences of immigrant Sri Lankan Tamil parents of children diagnosed with ASD in Southern Ontario, Canada. Method: Interviews were analyzed using an in-depth content analysis. Findings: Results demonstrated parents’ perceived supports and barriers towards ASD intervention planning, and indicated that parents were generally satisfied by the level of cultural competence in current ASD systems. However, families may still experience significant immigrant-related barriers that are not fully addressed. Implications: Recommendations to improve cultural awareness among occupational therapists utilizing ASD interventions are suggested.

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)0.003
metaresearch head score (Gemma)0.003
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 score0.384
Threshold uncertainty score0.763

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0230.008
Scholarly communication0.0040.002
Open science0.0020.008
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.389
GPT teacher head0.427
Teacher spread0.038 · 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

Citations19
Published2022
Admission routes2
Has abstractyes

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