“Filling in the gap”: A qualitative case study about identity construction of siblings of youth with a neurodisability
Bibliographic record
Abstract
INTRODUCTION: In families of children with a neurodisability, siblings have unique experiences that can shape their identity. There is limited information about the developmental process of how siblings form their identity. This study aims to understand the identity construction of young siblings who have a sibling with a neurodisability. METHODS: As part of a patient-oriented research program, we engaged with our Sibling Youth Advisory Council in Canada. In this qualitative case study, data from semi-structured interviews augmented by photo elicitation and graphic elicitation of relational maps were analyzed using reflexive thematic analysis. RESULTS: Nineteen sibling participants (median age = 19 years, range = 14-33 years) reflected on the uniqueness of their role during childhood. During adolescence and emerging adulthood, they became closer with their sibling with a neurodisability and increased communication with their parents about how to care for their sibling with a neurodisability. These experiences influenced how they explored and began to reconcile their sibling identity with their professional and social identities. CONCLUSION: Siblings of youth with a neurodisability discover their unique identity and require support in this developmental process. Future interventions could evaluate how supports for siblings can have an impact on the positive development of their identity.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".