Submission to the House Standing Committee on Health, Aged Care and Disability inquiry into the Thriving Kids initiative
Bibliographic record
Abstract
This submission draws on expertise and lived-experiences across the University of Melbourne with respect to disability, learning difficulties, autism, early childhood and community and early and primary education settings, and workforce strengths and challenges (e.g., teachers, allied health professionals). It also draws heavily on previous enquiries in related fields, as follows: • Select Committee on Autism. (2022). Services, support and life outcomes for autistic Australians (Executive summary). Parliament of Australia https://www.aph.gov.au/Parliamentary_Business/Committees/Senate/Autism/autism/Report • Classroom strategies for Autistic Students and Students with ADHD. Findings from an umbrella review, draft September, 2025 • The review of best practice in early childhood intervention and development of the new National Best Practice Framework for Early Childhood Intervention, launched in September 2025 by the Department of Health, Disability and Ageing • Melbourne Graduate School of Education Submission to the Australian Government's Early Years Strategy (prepared by REEaCH Centre) • OECD Good practices in delivering integrated care- examples from the Netherlands, Denmark, France and Ontario. 2023, Output 4. • Educational and Developmental Psychology experience with the Helping children with Autism fund (ended with NDIS), used for assessment, allied health support (e.g., Autism Queensland). • ACECQA Development of Inclusive Practice Framework • Working Together to Deliver the NDIS: Final report of the Independent Review of the National Disability Insurance Scheme Alongside previous enquires in related fields, this report also draws upon the expertise from across various academic groups, research centres and hubs at the University of Melbourne, that each focus on children and families in various ways: • The Learning Intervention Academic Group: https://education.unimelb.edu.au/research/academic-groups/learning-intervention • The University of Melbourne Neurodiversity Project: https://www.unimelb.edu.au/neurodiversity • Centre for Wellbeing Science: https://education.unimelb.edu.au/cws • Research in Effective Education in Early Childhood (REEaCH): https://education.unimelb.edu.au/REEaCh • Melbourne Disability Institute: https://disability.unimelb.edu.au • Learning Environments Applied Research Network (LEaRN): https://sites.research.unimelb.edu.au/learn-network Given the research and professional expertise of the contributing authors, we have decided to focus on three of the six terms of reference: • Term of reference 2: Examine the effectiveness of current (and previous) programs and initiatives that identify children with development delay, autism or both, with low to moderate support needs and support them and their families. This examination should focus on community and mainstream engagement, and include child and maternal health, primary care, allied health, playgroups, early childhood education and care and schools. • Term of reference 5: Draw on domestic and international policy experience and best practice. • Term of reference 6: Identify mechanisms that would allow a seamless transition through mainstream systems for all children with low to moderate support needs.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".