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Record W4255870577 · doi:10.24124/2013/bpgub931

ARTivism: Gender and artistic expression at AWAC.

2013· dissertation· en· W4255870577 on OpenAlexaff
Reeanna Bradley

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsCanadian HeritageLibrary and Archives Canada
Fundersnot available
KeywordsSubordination (linguistics)Gender studiesNormativeSociologyHuman sexualityDisadvantagePower (physics)IndigenousExpression (computer science)The artsVisual artsPolitical scienceArt

Abstract

fetched live from OpenAlex

This thesis explores the power dynamics inherent in discussions about legitimate knowledge and gender expectations. Through eight sessions of art and eleven interviews, it exposes oppressive systems and compares the intersections of race, class, sex, and sexuality. My interdisciplinary approach expands from the work of local contemporary artist and researcher Zandra Dahne Harding. Building upon her thesis, and including influences from feminist theorists such as Rich, hooks, and Butler, and minority activists like Tuhiwai Smith and Feinberg, I situate voices emerging from marginalized populations as equally relevant and poignant, using the case study of seventeen residents of AWAC Homeless Shelter. Art is a means of expression for those whose experiences are muted by socioeconomic disadvantage, differential access to education, and non-normative gender identities. This thesis shares an example of how oppressed people can use and personalize participation in the visual arts to subvert elements of prevailing power structures, like those related to education, criminal corrections, and gender hierarchies. Art sessions and interviews conducted with feminist and indigenous frameworks, called artivism' helped participants involved with a street-level shelter in Northern British Columbia communicate some aspects of their diverse truths of subordination. --Leaf 2.

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 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)0.002
metaresearch head score (Gemma)0.002
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.175
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.244
GPT teacher head0.545
Teacher spread0.301 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2013
Admission routes1
Has abstractyes

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