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Record W3086278079 · doi:10.1111/1467-9566.13184

‘We're responsible for the diagnosis and for finding help’. The help‐seeking trajectories of families of children on the autism spectrum

2020· article· en· W3086278079 on OpenAlexafffundabout
Isabelle Courcy, Catherine des Rivières‐Pigeon

Bibliographic record

VenueSociology of Health & Illness · 2020
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalUniversité du Québec à Montréal
FundersFonds de Recherche du Québec - SantéSocial Sciences and Humanities Research Council of Canada
KeywordsAutismSpectrum (functional analysis)PsychologyAutism spectrum disorderDevelopmental psychologyPhysics

Abstract

fetched live from OpenAlex

This article focuses on parents' process of seeking help for their child when a diagnosis of autism spectrum disorder is made or suspected. The study was conducted with 18 parents of children aged 4-10 years in Quebec (Canada). A trajectory-network approach was applied in order to carry out an in-depth analysis of family help-seeking trajectories based on the relationships mobilised (or neglected) over time and on life course events that may have precipitated (or hindered) help-seeking actions. Semi-directed interviews based on a name generator were conducted. A qualitative analysis of the content of family narratives was done and followed by the production of a schematic representation of each families' help-seeking trajectory. The results identified four constitutive phases during which relationships within the family, within associations, or with health and social services or education professionals helped or hindered the help-seeking process. The results show the relevance of the proposed approach for analysing the help-seeking process and better supporting families of children on the autism spectrum.

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)0.005
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 score0.420
Threshold uncertainty score0.836

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.010
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.108
GPT teacher head0.366
Teacher spread0.258 · 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

Citations14
Published2020
Admission routes3
Has abstractyes

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