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Record W2789708143 · doi:10.1080/14780887.2018.1429863

Using found poetry to illuminate the existential and posttraumatic growth of women with breast cancer engaging in art therapy

2018· article· en· W2789708143 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueQualitative Research in Psychology · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsMcGill UniversityConcordia University
FundersRéseau de recherche portant sur les interventions en sciences infirmières du Québec
KeywordsExistentialismPoetryThe artsEvocationCreative writingLived experiencePsychologyAestheticsSociologyPsychoanalysisPsychotherapistVisual artsArtEpistemologyLiteratureAnthropologyPhilosophy

Abstract

fetched live from OpenAlex

Arts-based research (ABR) is an expanding methodological genre, which adapts the tenets of the creative arts to make social science research accessible, evocative, and engaging. It crosses the boundaries of both art and science, but has made few inroads within the discipline of psychology. This article describes a pilot project examining how art-making shaped the trajectories of women diagnosed and treated for breast cancer. Using ABR as a way of distilling the findings, we demonstrate how experiences of existential and posttraumatic growth can be understood more intensely and profoundly through found poetry. Found poems (excerpts from interviews reframed as poetry) offer a richer, more meaningful, and potent evocation of themes than traditional coding categories. Poetry permits the voice of the participant to be more clearly heard and allows the reader to access deeper insights and understandings of the complexities of growth through adversity.

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)0.004
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.715

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.439
GPT teacher head0.578
Teacher spread0.140 · 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