Capacity Building goals in young people with cerebral palsy in Australia: Analysis of publicly available National disability Insurance Scheme data
Bibliographic record
Abstract
Background The Australian National Disability Insurance Scheme (NDIS) aims to provide person-centred care for individuals with disabilities, promoting independence and societal participation. Capacity Building supports are critical for young adults with cerebral palsy (CP) to develop essential lifelong skills. Methods A retrospective cross-sectional analysis was conducted using publicly available NDIS Participant and Payment datasets from the June 2023 quarter. Data for young adults with CP aged 15–34 years were extracted and analysed to examine characteristics and funding allocations for Capacity Building goals, with comparisons to peers with Down syndrome and spinal cord injury (SCI). Results 99.5 % (n = 6,273) of NDIS participants aged 15–34 with CP identified at least one Capacity Building goal, totalling 110,234 goals. Average annual payments for Capacity Building supports increased with age, from $27,000 for those aged 15–18 to $59,000 for those aged 25–34. The most frequent Capacity Building goals identified were ‘Daily Living’, ‘Social and Community Participation’, and ‘Health and Wellbeing’. Variations were observed in the types and funding allocation of Capacity Building supports accessed by young adults with CP compared to peers with Down syndrome and SCI. Conclusion This study highlights variability in NDIS funding allocation for young adults with CP as they transition into adulthood, emphasising the need for tailored funding strategies. Individualised goal setting and supports align with international best practices, enhancing independence and quality of life. Further research is needed to evaluate the outcomes of NDIS-funded supports, ensure equitable resource distribution, and inform global discussions on inclusive policies for people with disabilities.
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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 | 0.010 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".