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Record W2944050666 · doi:10.1177/1367549419839877

Investigating politics through artistic practices: Affect resonance of creative publics

2019· article· en· W2944050666 on OpenAlexaffabout
Tara Mahoney, Frédérik Lesage, Peter Zuurbier

Bibliographic record

VenueEuropean Journal of Cultural Studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPoliticsAgency (philosophy)Citizen journalismCitizenshipAffect (linguistics)PublicsSociologyPublic relationsAestheticsCivic engagementMedia studiesPolitical scienceSocial scienceLawArt

Abstract

fetched live from OpenAlex

While artistic practices have been central to political movements throughout the 20th century, much analysis treats these modes of expression as distinct or separate from more traditional forms of civic practices and everyday political participation. Building on discussions of the cultural turn in civic agency and the shortcoming of cultural citizenship, the authors of this article interrogate the relationship between affect, artistic practices and participatory politics. We discuss the findings from a research project in which the researchers worked with artist-facilitators involved in a community engagement initiative around the 2015 Canadian Federal Election. The investigation made use of an innovative combination of qualitative methods including probe-based research methods to better understand how participatory artistic practices can play a role in the election cycle. Through an account of our investigation conducted with these artists, we explore the role of artistic practices and emotion in navigating the distinctions between politics and the political in everyday life.

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)0.003
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.009
Scholarly communication0.0080.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.162
GPT teacher head0.415
Teacher spread0.253 · 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

Citations6
Published2019
Admission routes2
Has abstractyes

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