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Record W7100058722

Partnerships for Arts Integration: Exploring the Experiences of Teachers and Artists Working with Integrated Arts Programs

2008· article· en· W7100058722 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicEnzyme Structure and Function
Canadian institutionsnot available
Fundersnot available
KeywordsThe artsArts in educationPreparednessVisual arts educationPerforming arts educationProfessional developmentPerceptionIndustrial arts
DOInot available

Abstract

fetched live from OpenAlex

i\\.bstract This research acknowledges the difficulties experienced by teachers presenting integrated arts curricula. Instructional support is offered by arts organizations that provide arts partnerships with local schools boards. The study focuses on the experiences of 8 teachers from a Catholic school board in southern Ontario who participated in integrated arts programs offered by The Royal Conservatory of Music's Learning Through the Arts ™ (LTTATM) program and a local art gallery's Art Based Integrated Learning (ABIL) program and examines their responses to the programs and their perception of personal and professional development through this association. Additionally, questions were posed to the."aftisfs"from-tneSe]Jfograrrrs;-and"they liiscus·sed·how "participating in-collaboration with teachers in the development of in-school programs enabled them to experience personal and professional development as well. Seven themes emerged from the data. These themes included: teachers' feelings of a lack of preparedness to teach the arts; the value of the arts and arts partnerships in schools; the role of the artists in the education of teachers;

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)0.013
metaresearch head score (Gemma)0.020
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 score0.029
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.020
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0290.019
Scholarly communication0.0150.009
Open science0.0040.021
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0060.001

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 head0.193
GPT teacher head0.272
Teacher spread0.079 · 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
Published2008
Admission routes1
Has abstractyes

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