Stress appraisal and coping in siblings of children with special needs
Bibliographic record
Abstract
Self-reports from siblings of children with special needs are considered important additions to the disability literature. Twelve sibling dyads from the greater Montreal area were interviewed. Participating siblings of children with special needs were between the ages of 8 and 12, with a mean age of 9.5 years. Siblings with special needs were a mean age of 10.08 years. Sibling daily hassles, uplifts, and coping strategies were examined and analyzed using descriptive statistics. Family coping strategies and parental assessments of sibling relationship quality was also assessed. Children reported that most frequent daily events were when their siblings with special needs cry, scream or yell when they do not want to do something, and when they give hugs or kisses. Siblings reported being most stressed when embarrassed by their siblings with special needs in front of friends, and happiest when playing together with their sibling with special needs. Wishful thinking was reportedly commonly used by all children as a coping strategy during stressful times. Sibling results were also assessed by age and gender. In addition, families reported using acceptance of stressful events to cope, whereas family support was minimally used. Parent perceptions of their children's sibling relationship were generally positive, with loyalty, sharing, and controlling behaviour reported occurring most commonly.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".