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Record W4280653311 · doi:10.1386/jaah_00100_1

Exploring artmaking as a source of metaphor for women’s cancer experiences: A phenomenological study

2022· article· en· W4280653311 on OpenAlexafffund
Christine Novy, Marie-Christine Ranger, Roanne Thomas

Bibliographic record

VenueJournal of Applied Arts and Health · 2022
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsUniversity of Ottawa
FundersCanada Research Chairs
KeywordsMetaphorContext (archaeology)Interpretative phenomenological analysisPsychologySociologyQualitative researchSocial sciencePhilosophyLinguisticsHistory

Abstract

fetched live from OpenAlex

Metaphoric language is common in cancer discourse. However, prevailing military and journey metaphors may not capture variation in cancer experiences. In this article, the authors describe an art-based community research programme for women who had experienced cancer. Taking a phenomenological approach, the article examines how artmaking processes and materials were used by the study participants to shape their own metaphoric thought and, thereby, to articulate a more intimate understanding of their cancer experiences. The authors discuss four themes arising from their findings: (1) experiencing metaphor at its source, (2) artworks as insight cultivators, (3) art as process and metaphor for understanding cancer and (4) alternative metaphors for the cancer experience. Artmaking may be a means to enhance phenomenological data collection in the context of cancer experiences. By capturing variation in women’s cancer experiences, it may also lead to improvements in cancer survivorship care.

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)0.006
metaresearch head score (Gemma)0.009
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 score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0120.019
Scholarly communication0.0070.007
Open science0.0020.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.198
GPT teacher head0.385
Teacher spread0.187 · 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

Citations2
Published2022
Admission routes2
Has abstractyes

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