Theoretical Model for Conceptualizing Cross‐Cultural Applications and Intervention Strategies for Parents of Children With Disabilities
Bibliographic record
Abstract
Abstract Theoretical models should provide a framework to facilitate parents’ developing effective life management strategies. This paper provides a brief overview of the research on parent effective life management and cross‐cultural issues for families with a child who has disabilities. The authors note that the ability of image‐making, meaning‐making, and choice‐making to facilitate outcome is clearly substantiated by research in the stress and coping literature. Using the parent transformational process model, the authors examined responses from 18 multicultural families to demonstrate how this model may go beyond description of relevant cross‐cultural family variables in making sense of research findings and conceptualizing meaningful, and appropriate intervention strategies for families of children with disabilities. The authors conclude that rather than a linear process, it is quite likely that the critical questions that parents deal with at the diagnosis of their child reappear at other child and family markers, requiring a reworking of images and meanings and provision of a new range of choices. Professionals should be aware that parental adjustments to disability are not always linear, and thus use this awareness to not judge parents and to serve as catalysts for continued positive life management and transformation throughout the family life cycle.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.014 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".