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Record W4399713638 · doi:10.32920/26046652

Spaces of Care / Photography as Queer Racialized Affective Archives: A Collaborative Project

2024· preprint· en· W4399713638 on OpenAlexaff
Pauline Nguyen

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsQueerPhotovoiceEphemeral keySociologyTheme (computing)FeelingGender studiesCitizen journalismThe artsAestheticsVisual artsMedia studiesArtPsychologySocial psychologyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

This participatory research-creation project brings together the photovoice method and queer personal archives to look at how the ephemeral, feelings-based aspects of queer and trans racialized young people's experiences of 'spaces of care' can be shared through photographmaking. Through the facilitation of four photovoice workshops with three other queer/trans racialized identified young people, each collaborator created 35mm photographs related to the theme 'spaces of care,' culminating in a collective zine. The process of coming together to share ideas, feelings, and experiences is as important as the making of artwork itself. In focusing on the archival possibilities that arise from a qualitative arts-based method (photovoice) that is not typically concerned with issues of the archive, this project simultaneously critiques photovoice and asks: how might affective attachments to spaces of (queer) care, as fundamentally ungraspable and ephemeral experiences, be brought into the queer archive through photographmaking?

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)0.013
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 score0.031
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0180.014
Scholarly communication0.0080.005
Open science0.0010.010
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.273
GPT teacher head0.624
Teacher spread0.350 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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Same topicParticipatory Visual Research MethodsFrench-language works237,207