MétaCan
Menu
Back to cohort
Record W3087970791 · doi:10.1111/jade.12319

Dissensus, Street Art and School Change

2020· article· en· W3087970791 on OpenAlexfundno aff
Bronwen Low, Melissa Proietti

Bibliographic record

VenueInternational Journal of Art & Design Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCritical Theory and Political Philosophy
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsThe artsGeneral partnershipVisual arts educationCurriculumSociologyNarrativeEthnographyPedagogyVisual artsPolitical scienceArt

Abstract

fetched live from OpenAlex

Abstract This article draws upon Rancière’s concepts of the ‘distribution of the sensible’ and ‘dissensus’ in order to explore some of the tensions and processes at work in a multi‐year school change project that sought to transform a school through the ‘urban arts’. Building on student interest in extracurricular Hip‐Hop and street art programming, the school tried to integrate the urban arts across the curriculum through a partnership with local arts organisations and university researchers. While there were a number of project successes, the project also faced significant resistance, which in Rancière’s terms might be inevitable since the project tried to transform the dominant ways of doing and making in the school, displacing those who no longer saw themselves reflected. We understand the tensions in light of the disruptive power of street art and Hip‐Hop culture, but also as manifestations of antiblackness in education. Using data from a three‐year critical ethnography, we share a series of narrative vignettes which unpack the role of the visual arts in challenging the distribution of the sensible at the school, and offer insight into how teachers might have been better invited in as participants in dissensus.

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)0.018
metaresearch head score (Gemma)0.026
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 score0.019
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0190.093
Scholarly communication0.0080.008
Open science0.0020.011
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.094
GPT teacher head0.392
Teacher spread0.297 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Art & Design EducationSame topicCritical Theory and Political PhilosophyFrench-language works237,207