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Record W1667312181

Opening the Conversation: An Investigation into the Interface of Drama Therapy, Intergenerational Trauma, and Aboriginal Youth of Canada

2015· dissertation· en· W1667312181 on OpenAlexaboutno aff
Mariah St. Germain

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2015
Typedissertation
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsDramaConversationIntervention (counseling)PopulationDrama therapyAction (physics)PsychologyPsychotherapistSociologyPsychiatryVisual artsArt
DOInot available

Abstract

fetched live from OpenAlex

This research paper aims to summarize an investigation that the researcher carried out by exploring the question: How can Intergenerational Trauma experienced by Aboriginal Youth be addressed within the context of Drama Therapy? The paper includes a literature review on the fundamental elements of Drama Therapy as a modality, trauma experienced as an intergenerational phenomenon, and an existing snapshot of Aboriginal youth in Canada from a historical-bibliographical lens. A discussion of intersections between the triangulation of population (Aboriginal Youth), issue (Intergenerational Trauma), and potential intervention (Drama Therapy) is then presented. This is followed by recommendations for moving forward with the momentum for action in this proposed scenario. The goal of this research seeks to yield an understanding of the need for such an intervention to exist and to provide a basis of rationale for the motivation of potential stakeholders to pursue such interest. Further, the researcher strives toward an illumination of the significance of contribution from the Creative Arts Therapies in the conversation and incentive for change concerning the findings from the Truth and Reconciliation Commission of Canada in this vein.

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)0.005
metaresearch head score (Gemma)0.008
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 score0.778

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0470.018
Scholarly communication0.0100.003
Open science0.0030.010
Research integrity0.0020.005
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 head0.051
GPT teacher head0.318
Teacher spread0.267 · 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
Published2015
Admission routes1
Has abstractyes

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