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Record W4393291078 · doi:10.58837/chula.jucr.9.1.3

Youth ARTivism: Fostering Civic Engagement Through Public Art

2014· article· en· W4393291078 on OpenAlexaboutno aff
Anjuli Solanki

Bibliographic record

VenueJournal of Urban Culture Research · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsCivic engagementPublic engagementSociologyPolitical scienceMedia studiesPublic relationsAestheticsArtPoliticsLaw

Abstract

fetched live from OpenAlex

The Sustainable Thinking and Expression on Public Space (STEPS) Initiative's Emerging ARTivist program provides a platform for young people from some of Canada's most diverse and low-income communities to animate public spaces in their communities. This program has not only improved the urban experiences of local City of Toronto residents, but has built the capacity of youth as civic leaders engaged in urban design issues; empowered to transform the their urban environment. Alongside their award-winning youth led arts collective (the Toronto Emerging ARTivists), the STEPS Initiative has led the installation of several large-scale permanent art, including the World's Tallest Mural, transforming Toronto's skyline, and a 400 linear foot Fence Reclamation Project along a pedestrian corridor. This paper will discuss lesson learned by STEPS, in their engagement of youth and residents of all ages in the conception, planning, and implementation of these projects.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.898
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.339
GPT teacher head0.375
Teacher spread0.036 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2014
Admission routes1
Has abstractyes

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