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Record W4402047291 · doi:10.46743/2160-3715/2024.6661

Virtual Cellphilming with GBTQ Pups: Towards Participant-Driven Research as Activism

2024· article· en· W4402047291 on OpenAlexaff
Kinda Wassef, O Bonardi, Megan Aston, Olivier Ferlatte, Phillip Joy

Bibliographic record

VenueThe Qualitative Report · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsDalhousie UniversityUniversité de MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalMount Saint Vincent University
Fundersnot available
KeywordsQueerSociologyReflexivityHeteronormativityNarrativeContext (archaeology)LegitimacyParticipatory action researchGeneral partnershipGender studiesPoliticsSocial sciencePolitical science

Abstract

fetched live from OpenAlex

In the present paper, we draw upon our research, entitled Puppy Philms, to guide researchers who are interested in queering cellphilming methodologies. In this context, “queering” refers to the process of challenging and disrupting heteronormative roles and perspectives within research practices. We argue that taking a queer poststructural approach to virtual cellphilming helped us shift this project away from typical academic relations of power, towards participant-driven research as activism. In emphasizing flexibility, reflexivity, a desire for partnership and community building, we found queer communication to be a mechanism through which we could shift power and drive levels of engagement. In considering the continued stigma associated with pup play, queer poststructuralism theories allow cellphilms to disrupt traditional norms, both societal and academic norms. We found that cellphilming is particularly suited for the study of queer eroticism because participants can control the narrative, deliver a more nuanced understanding of the experiences portrayed, and claim legitimacy through association with an arts-based participatory research project.

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)0.061
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0610.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.896
GPT teacher head0.778
Teacher spread0.118 · 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; both teacher heads agree on what is shown here.

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
Published2024
Admission routes1
Has abstractyes

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