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Record W3012190005 · doi:10.3138/tric.40.1_2.64

A Small Festival for Small People: The WeeFestival as Advocacy

2019· article· en· W3012190005 on OpenAlexvenueaboutno aff
Heather Fitzsimmons Frey

Bibliographic record

VenueTheatre Research in Canada · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsThe artsPublic sphereSociologySpace (punctuation)Action (physics)WatsonVisual artsPublic relationsPublic spaceMedia studiesAestheticsArtPolitical scienceLawEngineeringPolitics

Abstract

fetched live from OpenAlex

The WeeFestival, English Canada’s first performance festival dedicated to children from ages 0 to 5, acts as an advocate for the early years demographic and for the artists who create for them through three key elements of festival structure: programming, space, and creative/artistic exchange. Engaging with research by Ben Fletcher-Watson, Lise Hovik, Matthew Reason, and Adele Senior, this article uses company archives, artist interviews, and the writer’s personal experiences to analyze how the WeeFestival temporarily establishes an alternative public sphere that challenges policy-makers, funders, and artists to rethink relationships between arts, very young citizens, and urban life. Even though very young citizens may not initially know that they want to experience art, the festival attends to the interests and responses of young people, demonstrates respect for their capacity to be emotionally and intellectually engaged by artful and thoughtful productions, and establishes festivalized spaces that put an alternative public sphere into action, gesturing to the possibility of real social change. Taking into account the significance of programming for artists, educators, and policy-makers alongside the significance of meaningful audience-artist exchange, the analysis suggests that events like the WeeFestival have the capacity to gently shift how urban dwellers perceive very young children and the way they interact with the arts in daily 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 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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.903
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.132
GPT teacher head0.389
Teacher spread0.256 · 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.

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

Citations1
Published2019
Admission routes2
Has abstractyes

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