Reading with Children on the Autism Spectrum: The Experiences of Bilingual Chinese Canadian Immigrant Families
Bibliographic record
Abstract
Much is known about the benefits of shared reading with typically developing children and the role of family in facilitating children’s language and literacy development. However, less is known about how parents of children on the autism spectrum experience reading with their children. In fact, to date there is little research on understanding the shared reading experiences of families of children on the autism spectrum, particularly from culturally and linguistically diverse (CLD) backgrounds. Research targeting this population is of critical importance, as it sheds light on unique experiences and can contribute to the design of culturally appropriate programs and interventions. This study, therefore, aimed to gain a deep understanding of the lived experiences of bilingual Chinese Canadian immigrant parents regarding reading with their children on the autism spectrum. Using Interpretative Phenomenological Analysis (IPA) as a methodological framework, this study recruited seven bilingual Chinese Canadian immigrant parents of children on the autism spectrum (aged 3-8). Data were collected through semi-structured interviews, journal entries, and follow-up interviews. The findings of within-case and cross-case analysis revealed a multifaceted nature of experiences of bilingual Chinese immigrant parents regarding reading with their children on the autism spectrum. Group Experiential Themes across cases included (1) aims and motivations, (2) shared reading practices, (3) barriers and challenges, and (4) strategies. This study contributes a unique qualitative perspective to the nascent body of research investigating shared reading with autistic children from CLD backgrounds.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.008 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".