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Record W2924945005 · doi:10.26443/crae.v46i1.49

Exploring a Curricula of Visual and Poetic Aesthetics / Exploration de programmes d’esthétisme visuel et poétique

2019· article· fr· W2924945005 on OpenAlexaffvenue
Kelly Young

Bibliographic record

VenueThe Canadian Review of Art Education / Revue canadienne d’éducation artistique · 2019
Typearticle
Languagefr
FieldArts and Humanities
TopicVisual Culture and Art Theory
Canadian institutionsTrent University
Fundersnot available
KeywordsPoeticsPoetryArtThe artsHumanitiesCurriculumVisual artsAestheticsSociologyLiteraturePedagogy

Abstract

fetched live from OpenAlex

Abstract: In this article, I explore the role of visual arts in shaping the future direction of the literary arts in my pre-service teacher education classroom. I outline a cross-curricular curriculum by exploring a theoretical and practical relationship between visual and poetic aesthetics. Drawing upon the imagination, we are able to become critical storytellers as we engage in ekphrastic poetics, that is—a poetic response to a form of art. Ultimately, we modify and expand on the practice to include responses to photography or works of art—that are themselves aesthetic responses. Key words: Arts; Education; Imagination; Ekphrastic Poetics; Curriculum. Résumé : J’analyse dans cet article le rôle des arts visuels dans l’orientation future des arts littéraires dans le contexte de ma classe de formation initiale des enseignants. Je donne un aperçu d’un programme transdisciplinaire en analysant le lien théorique et pratique entre l’esthétisme visuel et l’esthétisme poétique. Nous pouvons, grâce à l’imagination, devenir des raconteurs critiques par le biais de la poésie ekphrasique, c’est-à-dire par le biais d’une réaction poétique vis-à-vis une forme d’art. En bout de ligne, nous modifions et élargissons la pratique pour y inclure les réactions face à la photographie ou à des œuvres d’art, qui sont elles-mêmes des interprétations esthétiques.Mots-clés : arts, éducation, imagination, poésie ekphrasique, curriculum.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.949
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.053
GPT teacher head0.302
Teacher spread0.249 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2019
Admission routes2
Has abstractyes

Explore more

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