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Record W2088050743 · doi:10.1177/1476750310396950

Successes and challenges of feminist arts-based participatory methodologies with homeless/street-involved women in Victoria

2011· article· en· W2088050743 on OpenAlexaff
Darlene E. Clover

Bibliographic record

VenueAction Research · 2011
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsEmpowermentThe artsSociologyCitizen journalismParticipatory action researchIdentity (music)Gender studiesStigma (botany)Collective identityMental healthPoliticsPublic relationsMedia studiesAestheticsVisual artsPolitical sciencePsychologyArt

Abstract

fetched live from OpenAlex

This feminist arts-based participatory research project with a group of homeless/street-involved women used group interviews and the creation of collective and individual artworks to explore their personal and political realities and share these with a larger audience. The project built trust and a sense of community, encouraged artistic skills development, and allowed to emerge an artistic identity to combat the stigma of the label ‘homeless’. Individual and collective empowerment came from creating artworks collectively but also, the recognition the women received through publicly sharing their artworks. Tensions and challenges emerged around art as education versus therapy, individual and collective works, the role and place of men, and mental health and the police, two things ever present in the lives of these women.

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)0.044
metaresearch head score (Gemma)0.024
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 score0.955
Threshold uncertainty score0.235

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0440.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0230.024
Scholarly communication0.0090.004
Open science0.0030.012
Research integrity0.0030.003
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 head0.706
GPT teacher head0.579
Teacher spread0.127 · 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

Citations92
Published2011
Admission routes1
Has abstractyes

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