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Record W2614787644 · doi:10.21810/sfuer.v8i.389

Re-instating the Amateur: Holding Space for the Core Purpose of Art in the Classroom

2015· article· en· W2614787644 on OpenAlexvenueno aff
Nicole Armos

Bibliographic record

VenueSFU Educational Review · 2015
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsnot available
Fundersnot available
KeywordsAmateurTransformative learningThe artsVisual arts educationSociologyValue (mathematics)PedagogyVisual artsArt methodologySpace (punctuation)Fine artContemporary artAestheticsArtPolitical scienceComputer science

Abstract

fetched live from OpenAlex

The methods and objectives for art education in public and post-secondary schools are often aimed towards the development of a professional fine arts or academic career. However, reflecting on the reasons humans originally turned to the arts can have profound effects on how we frame the role of the artist, art educator, student, and classroom. This paper traces perspectives on the core purpose of art from fields ranging from biology and anthropology to education and literary theory, noting how they converge on notions of art as an evolutionary form of social bonding, and open-ended life inquiry for personal and social transformation. Drawing from these theories, it discusses how these transactional perspectives on art reinforce the value of exposing students to both creative and interpretative forms of aesthetic inquiry. Further it proposes that the figure of the amateur artist—as opposed to that of the professional artist or renowned academic—can serve as an embodiment of the core purpose of art and our educational goals in the art classroom, encouraging students from diverse career paths to actively seek out meaningful and transformative art-making and appreciating experiences.

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)0.004
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0020.010
Scholarly communication0.0050.005
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.241
GPT teacher head0.483
Teacher spread0.242 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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