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Record W4402923344 · doi:10.1177/13505068241274971

Drawing as collective self-care: Leeds animation workshop’s collaborative practices during the pandemic

2024· article· en· W4402923344 on OpenAlexafffund
Rosanna Maule

Bibliographic record

VenueEuropean Journal of Women s Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsConcordia University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPandemicAnimationCoronavirus disease 2019 (COVID-19)SociologyMedia studies2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Visual artsMedicineArt

Abstract

fetched live from OpenAlex

Studies and debates about the impact of the Covid-19 (Covid-19 is the term widely used to denote the SARS-CoV-2 virus and adopted by the World Health Organization when communicating with the public) pandemic on the film and moving image industry have emphasized the economic and cultural consequences of lockdowns and social restrictions on cinematic productions and theatrical and festival circuits, leading to the rise of streaming platforms and services. Within this discussion, little attention has been drawn to the independent sector of non-profit cooperatives or collectives, grassroots distribution companies and community archives involved in feminist and lesbian, gay, bisexual, transgender, queer, intersex and asexual+ activism. This essay examines this area of post-pandemic cinema through the example of Leeds Animation Workshop, a women-run, feminist collective. Since its establishment in the eponymous West-Yorkshire city in 1978, the collective has been producing and distributing gender-focused animation films about social and educational issues worldwide. My argument is that Leeds Animation Workshop’s online media activities during the pandemic signal less an adjustment to a new media environment in response to social restrictions than a repurposing of their gendered and participatory media practices for social change and critical intervention.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.059
GPT teacher head0.349
Teacher spread0.289 · 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 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 routes2
Has abstractyes

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