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Record W1999615223 · doi:10.1177/0733464808330822

One Story at a Time

2009· article· en· W1999615223 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Applied Gerontology · 2009
Typearticle
Languageen
FieldPsychology
TopicCounseling, Therapy, and Family Dynamics
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsNarrativeStorytellingAddictionNarrative therapyPsychological interventionPsychologyEthnographyNarrative inquiryPsychotherapistMedicineGerontologyPsychiatrySociology

Abstract

fetched live from OpenAlex

Various factors including social isolation and financial worries put older adults at risk for addictions. Indeed, older adults are the largest consumers of medication, and alcohol consumption is rising. Yet interventions are limited and problems often go unreported. Unearthing “problem” stories in people’s lives (i.e., “the addiction story”) and retelling them in more empowering ways, narrative therapy offers a viable therapeutic alternative, and research on narrative therapy has proven encouraging. However, little is known about narrative therapy with older adults and with addictions. Seeking to address these gaps, an ethnographic study was conducted in Toronto, Canada, with a group of older adults receiving narrative therapy for addictions. Findings suggest that the therapy was “helpful” and participants were able to reduce or halt their substance misuse. Most important, aspects of narrative therapy such as storytelling may be particularly well suited to older adults, offering powerful possibilities for applied gerontology.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.459
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.024
GPT teacher head0.291
Teacher spread0.267 · 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