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Record W6986821151

Reading Development: Exploring the Lived Experiences of Individuals with High Functioning Autism

2018· dissertation· en· W6986821151 on OpenAlexaff

Bibliographic record

VenueQSpace (Queen's University Library) · 2018
Typedissertation
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsQuality (philosophy)PopulationReading (process)GloomStaring
DOInot available

Abstract

fetched live from OpenAlex

Reading expands learning opportunities for individuals with Autism Spectrum Disorder (ASD) by improving their communication and functional skills, and, in the long run, improving their quality of life. Research is needed to gain a better understanding of how individuals with autism experience their reading development from their own perspectives and the perspectives of their parents. Our knowledge of the experiences of individuals with ASD can be expanded by listening to and reflecting on their voices. Therefore, this study empowered four young adults with High Functioning Autism (HFA) and their parents to share stories and experiences about these young adults’ reading development from early childhood through adolescence. A qualitative multiple-case design was used. Data sources included eight one-on-one semi-structured interviews, researcher’s field notes, and a reflective journal. Qualitative analysis led to eight emergent cross-case themes: 1) differences and similarities in reading profiles, 2) advantage in expository text, 3) challenges in reading, 4) reading strategies, 5) behaviour support, 6) interest and motivation, 7) supportive parents, and 8) different school experiences. Based on rich, in-depth descriptions, this study sheds light on the diverse and varied experiences of four young adults with HFA in their reading development from early childhood through adolescence. The findings of this study help to fill the gap by adding voices of individuals with HFA and their parents. The findings provide researchers with recommendations on case study design and interviews with individuals with HFA, educators with suggestions for instructional practices, and parents with practical guidance.

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)0.006
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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.006
Scholarly communication0.0030.004
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.226
Teacher spread0.201 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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