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Record W4405455424 · doi:10.1177/10784535241303496

The Exploration of Art Creation Among Mothers from Ontario, Canada, with Histories of Gender-Based Violence Using an Interpretive Description Approach

2024· article· en· W4405455424 on OpenAlexafffundabout
Madison Broadbent, Kimberley T. Jackson, Tara Mantler

Bibliographic record

VenueCreative Nursing · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsWestern University
FundersWestern University
KeywordsEmpowermentStorytellingIntersectionalityPopulationPsychologySociologyDevelopmental psychologyGender studiesPolitical scienceDemography

Abstract

fetched live from OpenAlex

Gender-based violence (GBV) is a human rights violation and an issue of gender inequality, with 35% of women globally experiencing GBV. Mothers who experience GBV are a unique population, with vast implications on their health. Artmaking can reduce these health effects due to the self-expression, emotional healing, empowerment, and social change which often occur. The purpose of this study was to understand the process of independently creating a visual art form for mothers in Ontario, Canada, with histories of GBV, as a reflection of their experience of GBV. An arts-based interpretive descriptive study informed by intersectionality was conducted with 13 mothers from Ontario with histories of GBV utilizing semistructured interviews. Two themes emerged: (1) creative processes and (2) storytelling experiences of GBV through art. The findings from this study highlight the process of art creation among mothers from Ontario who have experienced GBV. However, further exploration surrounding artmaking among mothers with histories of GBV in Canada is warranted.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.178
Threshold uncertainty score0.358

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0190.012
Scholarly communication0.0060.002
Open science0.0020.004
Research integrity0.0010.002
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 head0.079
GPT teacher head0.276
Teacher spread0.197 · 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

Citations1
Published2024
Admission routes3
Has abstractyes

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