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Record W2761400647 · doi:10.36510/learnland.v9i2.762

Commentary: Urban Arts Pedagogy at James Lyng High School

2016· article· en· W2761400647 on OpenAlexaffvenueabout
Melissa Proietti

Bibliographic record

VenueLEARNing Landscapes · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsMcGill University
Fundersnot available
KeywordsThe artsCurriculumSociologyPedagogyVisual arts educationVisual artsArt schoolSpace (punctuation)Art

Abstract

fetched live from OpenAlex

Melissa Proietti is a PhD student at McGill University as well as a youth worker and street art coordinator at James Lyng High School in Montreal. In this interview, she describes an urban arts pedagogy project at the school. In its rst year, the students, in collaboration with McGill and various community groups, created a gallery space in the school and held their rst exhibit. Ms Proietti talks about the advantages of incorporating urban arts in the school curriculum and the lessons she learned from working with students on the project.

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)0.008
metaresearch head score (Gemma)0.040
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.224
Threshold uncertainty score0.446

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.040
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0230.011
Scholarly communication0.0070.009
Open science0.0070.005
Research integrity0.0560.090
Insufficient payload (model declined to judge)0.0110.004

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 head0.018
GPT teacher head0.250
Teacher spread0.232 · 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
GenreCommentary

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
Published2016
Admission routes3
Has abstractyes

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