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Record W7133064009

I Do It Because It’s Cool: The Positive Impact of Theatre Production and Design Courses in the Ontario Curriculum

2024· dissertation· W7133064009 on OpenAlexaboutno aff
Emma Teresa Pressello

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumProduction (economics)Curriculum developmentEmergent curriculumCurriculum theory
DOInot available

Abstract

fetched live from OpenAlex

This research investigates how applied theatre programming can foster a creative environment in secondary schools. Furthermore, it explores how the introduction of theatre production to high school students can be beneficial to the theatre community and why now is the right time to do so. I address these questions by compiling resources to create my own curriculum for an applied based theatre course and discover how it can be integrated into the Ontario school system. I have consulted various secondary sources and scholars, including a review of the Ontario curriculum documents. It is important to research this now as the post-pandemic educational world is a prime opportunity to reconstruct the secondary school curriculum to embed practice-based learning that can serve various industries, including the theatre world. The overarching goal is to determine how such programming can improve the industry as well as the interest and social-emotional growth of students and educators alike.

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)0.009
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 score0.107
Threshold uncertainty score0.455

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0110.005
Scholarly communication0.0070.002
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.037
GPT teacher head0.329
Teacher spread0.292 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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