Experiences of parents of children with special needs at school entry: a mixed method approach
Bibliographic record
Abstract
BACKGROUND: The transition from pre-school to kindergarten can be complex for children who need special assistance due to mental or physical disabilities (children with 'special needs'). We used a convergent mixed method approach to explore parents' experiences with service provision as their children transitioned to school. METHODS: Parents (including one grandparent) of 37 children aged 4 to 6 years completed measures assessing their perceptions of and satisfaction with services. Semi-structured interviews were also conducted with 10 parents to understand their experience with services. RESULTS: Post transition, parents reported lower perceptions of services and decreased satisfaction than pre-transition. The following themes emerged from the qualitative data: qualities of services and service providers, communication and information transfer, parent advocacy, uncertainty about services, and contrasts and contradictions in satisfaction. The qualitative findings indicate that parents were both satisfied and concerned with aspects of the post-transition service provision. CONCLUSIONS: While the quantitative results suggested that parents' experience with services became less positive after their children entered school, the qualitative findings illustrated the variability in parents' experiences and components of service provision that require improvements to facilitate a successful school entry.
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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 | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".