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Record W3111079640 · doi:10.3138/tric.41.2.f03

Staging Anxiety in Rachel Aberle’s <i>Still/Falling</i>

2020· article· fr· W3111079640 on OpenAlexaffvenueabout
M. J. Tomkinson

Bibliographic record

VenueTheatre Research in Canada · 2020
Typearticle
Languagefr
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHumanitiesPhilosophyArt

Abstract

fetched live from OpenAlex

Still/Falling (2016) est une pièce jeune public écrite par Rachel Aberle et produite par la compagnie Green Thumb Theatre de Vancouver. Dans cette contribution au forum, Matthew Tomkinson propose un examen critique du rôle de la pièce au sein du curriculum d’une école secondaire en s’attardant à trois aspects : les défis d’ordre pédagogique, la représentation sur scène et la terminologie employée. Tomkison fait valoir qu’un certain nombre d’éléments — des questions qui figurent dans le guide pédagogique, des symboles employés pour représenter la maladie mentale dans la pièce, le métadiscours sur la santé mentale — vont à l’encontre de la mission de Green Thumb, qui est de lutter contre la stigmatisation des maladies mentales. Selon lui, il faudrait mieux nuancer et développer le propos afin de combattre les stéréotypes.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.432
Threshold uncertainty score0.869

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0090.009
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.133
GPT teacher head0.342
Teacher spread0.209 · 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".

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Citations1
Published2020
Admission routes3
Has abstractyes

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