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Record W2150411782 · doi:10.1177/1049732304272914

An Application of the Transactional Model to the Analysis of Chronic Illness Narratives

2005· article· en· W2150411782 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueQualitative Health Research · 2005
Typearticle
Languageen
FieldPsychology
TopicTransactional Analysis in Psychotherapy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNarrativeCoping (psychology)Transactional leadershipTransactional analysisPsychologyCognitionNarrative inquiryContent analysisMeaning (existential)Clinical psychologyPsychotherapistDevelopmental psychologySocial psychologyPsychiatrySociology

Abstract

fetched live from OpenAlex

The authors' aim in this study was to describe the chronic illness experience and its relationship to the concept to finding meaning. They conducted interviews using a narrative approach with 15 adults experiencing various chronic illnesses and analyzed narrative data using a combination of holistic-content and categorical-content approaches. The three major categories were the context of the chronic illness experience, personal reactions, and coping efforts. These categories were best interpreted in terms of a transactional model. The authors categorized finding meaning under cognitive coping strategies and described it as a strategy that was part of a larger coping repertoire.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.747
Threshold uncertainty score0.730

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.265
GPT teacher head0.615
Teacher spread0.351 · 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