Analysing family service needs of typically underserved families in the USA
Bibliographic record
Abstract
BACKGROUND: Present day service systems evolved from the traditional model of disability intervention where the child with the disability and the family were viewed as pathological entities that needed to be fixed rather than supported. Scholars have increasingly called for a greater focus on the family in service delivery, but few studies have empirically examined the practical reality of such a shift. The present paper examines the disability-related formal service supports within the family quality of life (FQOL) framework in a sample of predominantly low-income, minority families in the USA. METHODS: Cross-sectional data collected from a convenience sample of 149 families using the Family Quality of Life Survey (FQOLS-2006) was analysed at the univariate, bivariate and multivariate levels. RESULTS: Over half of the families indicated that they needed more help from the service system, and the largest barrier to accessing services was a lack of information. Almost all families viewed service support as very important to their overall FQOL; however, only half of them were satisfied with the formal support that they were receiving. Less than half of the families reported having many service support opportunities and high attainment of service support, although most took high initiative in pursuing formal supports. The path model illustrated the complex inter-relationships between the six dimensions of service support. CONCLUSIONS: Findings underscore the need for resources to empower families and the value of using the FQOLS-2006 to ascertain the service support needs and strengths of families.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".