Predictors of Relationship Outcome between Disabled and Non-Disabled Siblings
Bibliographic record
Abstract
In recent years, there has been increasing research on individuals with a disabled sibling looking at the impact of the relationship on the adjustment and behaviour of the non-disabled sibling and predictors of sibling relationships such as behaviour disabled sibling. Although research to date has focused on individual factors, there is a need for research on the relative contributions of multiple factors. The purpose of this study is to understand the sibling relationship outcome between a disabled and non-disabled sibling as predicted by the stressors caused by the disabled sibling, the non-disabled sibling’s relationship perception and available coping and resources. This study will use the ABCX model (McCubbin & Patterson, 1983) as a framework to study predictors of relationship outcome between disabled and non-disabled siblings. Predictor variables will include: stress, aA factor, (demographic information and behaviour of sibling with a disability), resources, bB factor (knowledge about disability and resource use), perceptions, cC factor (self-efficacy and comfort with disabled sibling) and outcome, xX factor (relationship quality). I hypothesize that when the non-disabled sibling is more comfortable and knowledgeable about the disability and has a higher level of self-efficacy and available resources, the relationship will be perceived more positively, improving relationship quality and leading to a positive relationship outcome. Participants will consist of approximately 100 individuals aged 16 – 26 who have a sibling with a developmental disability. Data will be collected through an online survey. The results of this study are valuable, as understanding what the predictors are that lead to a positive versus negative relationship outcome is the first step in helping to intervene in the relationship and input the right implementations to ensure a positive outcome
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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 | 0.007 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".