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Record W2023495816 · doi:10.1093/hsw/34.2.97

The Many Layers of Social Support: Capturing the Voices of Young People with Spina Bifida and Their Parents

2009· article· en· W2023495816 on OpenAlexaff
Beverley J. Antle, G.W.G. Montgomery, C. Stapleford

Bibliographic record

VenueHealth & Social Work · 2009
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSpina bifidaSocial supportPsychologyPsychosocialDevelopmental psychologyInterpersonal relationshipPerspective (graphical)Qualitative researchInsiderSocial psychologyMedicineSociologyPsychiatry

Abstract

fetched live from OpenAlex

Young people with physical disabilities experience greater difficulty than their able-bodied peers in many psychosocial domains as they transition toward adulthood. However, firsthand knowledge of the dimensions of social support that young people with physical disabilities find useful during this stage is lacking. This qualitative study involved 50 participants (21 youths with spina bifida and 29 parents) and focused on gaining an insider's perspective on the nature of social support. Building on the work of LaGreca, themes were mapped into four broad support domains: tangible, information, companionship/belonging/mutuality, and emotional. This research indicates that parents provide substantial all-purpose support in each of the four domains. A second major finding shows that support from peers and friends follows a unique and varied path with distinctive characteristics related to the realities of living with a disability. Implications for social work practice with targeted populations and systems are considered.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.031
GPT teacher head0.354
Teacher spread0.323 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations34
Published2009
Admission routes1
Has abstractyes

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