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Record W4281666755 · doi:10.1007/s13384-022-00536-1

Possibilities and problems of using drama to engage with First Nations content and concepts in education: A systematic review

2022· review· en· W4281666755 on OpenAlexaboutno aff
Danielle Hradsky, Rachel Forgasz

Bibliographic record

VenueThe Australian Educational Researcher · 2022
Typereview
Languageen
FieldArts and Humanities
TopicCreative Drama in Education
Canadian institutionsnot available
FundersMonash University
KeywordsDramaEmbodied cognitionPedagogyDignityContent (measure theory)SociologySpace (punctuation)Public relationsEngineering ethicsPsychologyPolitical scienceEpistemologyEngineeringLawVisual artsArt

Abstract

fetched live from OpenAlex

Abstract Educators around the world are increasingly considering and seeking ways to challenge their role in the colonial project. Some have turned to embodied pedagogies as a way to encourage holistic, relationships-based learning in academies which traditionally prioritise cognitive, objective knowing. This review analyses 27 studies, published between 2007 and 2020, that draw on drama-based pedagogies to engage with First Nations content and concepts in early childhood, primary, secondary, and tertiary institutions. We found that drama provides powerful but often risky and unpredictable ways to enhance student, educator, and community learning, engagement, emotions, and relationships. The educator’s role is vital to enabling or preventing outcomes which contribute to the survival, dignity, and well-being of First Nations peoples. Ethical guidelines and issues must be carefully considered by anyone attempting to work in this complex, awkward space.

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)0.028
metaresearch head score (Gemma)0.117
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.028
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.117
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.005
Bibliometrics0.0170.016
Science and technology studies0.0010.002
Scholarly communication0.0050.005
Open science0.0020.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.370
GPT teacher head0.450
Teacher spread0.081 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations3
Published2022
Admission routes1
Has abstractyes

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