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Record W2119738435 · doi:10.1177/1049732302239598

Turning Points and Protective Processes in the Lives of People With Chronic Disabilities

2003· article· en· W2119738435 on OpenAlexaff
Gillian King, Tamzin Cathers, Elizabeth Gaspar Brown, Jacqueline Specht, Colleen Willoughby, Janice M. Polgar, Elizabeth MacKinnon, Linda K. Smith, Lisa Havens

Bibliographic record

VenueQualitative Health Research · 2003
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsThames Valley Children's Centre
Fundersnot available
KeywordsMeaning (existential)PsychologyQualitative researchPsychological resilienceMeaning-makingTurning pointSocial psychologyPsychology of selfDevelopmental psychologyPsychotherapistSociologyAesthetics

Abstract

fetched live from OpenAlex

In this qualitative study, the authors examined the nature of resilience in people with chronic disabilities. Fifteen people with disabilities identified the factors that helped or hindered them at major turning points, and the triggers and resolutions to these turning points. Turning points were emotionally compelling experiences and realizations that involved meaning acquired through the routes of belonging, doing, or understanding the self or the world. The major protective factors were social support, traits such as perseverance and determination, and spiritual beliefs. Three new protective processes were identified: replacing a loss with a gain (transcending), recognizing new things about oneself (self-understanding), and making decisions about relinquishing something in life (accommodating). These protective factors, processes, and ways in which people with disabilities draw sense and meaning in life have important implications for service delivery.

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)0.010
metaresearch head score (Gemma)0.022
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 score0.012
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0120.024
Scholarly communication0.0050.008
Open science0.0020.011
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.252
GPT teacher head0.592
Teacher spread0.340 · 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

Citations155
Published2003
Admission routes1
Has abstractyes

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