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Record W4413930899 · doi:10.1080/10705422.2025.2554884

“We Do Not Choose This Life”: Advocating for and Empowering Those Living with Poverty Through Applied Theatre

2025· article· en· W4413930899 on OpenAlexafffund
Carol A. Stalker, Ginette Lafrenière, Rachel Yavnai, Catherine Frid

Bibliographic record

VenueJournal of Community Practice · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsNutreco (Canada)Wilfrid Laurier University
FundersOntario Arts CouncilCatherine Donnelly Foundation
KeywordsPovertyEconomic growthSociologyPolitical scienceEnvironmental ethicsEnvironmental planningEnvironmental scienceEconomics

Abstract

fetched live from OpenAlex

A collaboration between a theatre company, a university and eight community organizations culminated in an applied theatre project entitled “Living Below the Line.” Residents living with poverty were invited to become co-creators of a new play, which was performed in five local venues. The project’s objectives were 1) the provision of a respectful, supportive, empowering and creative process for the co-creators, and 2) increased understanding of the effects of poverty for audience members and the larger community. This paper reports the findings of the evaluation, which indicate that the objectives were met in several ways: 1) the co-creators felt uplifted by the support of their colleagues and the positive response from the community; 2) they felt their stories of lived experience were respected, and they appreciated the opportunity to learn new skills; 3) the audiences reported increased awareness and understanding of the issues leading to poverty while being simultaneously deeply moved and entertained. Analysis of the findings indicate that skillful management of the ethical issues and sensitive accommodation of the co-creators’ physical, mental and emotional challenges were key to the success of 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)0.011
metaresearch head score (Gemma)0.015
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 score0.014
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0140.019
Scholarly communication0.0070.005
Open science0.0020.016
Research integrity0.0030.006
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 head0.045
GPT teacher head0.318
Teacher spread0.274 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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