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Record W6893959710 · doi:10.5281/zenodo.5803477

AGENTS FOR CHANGE

2021· article· pt· W6893959710 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typearticle
Languagept
FieldPsychology
TopicScience Education and Perceptions
Canadian institutionsnot available
Fundersnot available
KeywordsExhibitionRepresentation (politics)Focus (optics)AnthropoceneMedia artsIntersection (aeronautics)Modernity

Abstract

fetched live from OpenAlex

Agents for Change/Facing the Anthropocene presented artworks in 2020 at THE MUSEUM Kitchener, Canada by women media artists working at the intersection of science, technology and art, with a focus on nature and ecological change – the greatest danger of our time. Responding to the global recognition of the importance of the creative voices and activism of women artists, this unique exhibition demonstrates progress towards improving gender representation in the media arts. Agentes para a Mudança / Enfrentando o Antropoceno apresentaram obras de arte em 2020 em O MUSEU Kitchener, Canadá, por mulheres artistas de mídia que trabalham na interseção de ciência, tecnologia e arte, com foco na natureza e na mudança ecológica - o maior perigo de nosso tempo. Em resposta ao reconhecimento global da importância das vozes criativas e do ativismo de mulheres artistas, esta exposição única demonstra o progresso no sentido de melhorar a representação de gênero nas artes da mídia.

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)0.009
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.067
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0090.013
Scholarly communication0.0150.010
Open science0.0020.010
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0670.010

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 head0.275
GPT teacher head0.396
Teacher spread0.121 · 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 designNot applicable
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
Published2021
Admission routes1
Has abstractyes

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