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The Subversive Art Therapist: Embracing Cultural Diversity in the Art Room

2000· article· en· W212007564 on OpenAlexaff
Lani Gerity

Bibliographic record

VenueArt Therapy · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsHamilton Health SciencesHamilton Regional Laboratory Medicine Program
Fundersnot available
KeywordsMulticulturalismVariety (cybernetics)Diversity (politics)Art therapyAestheticsValue (mathematics)SociologyCultural diversitySpace (punctuation)Assimilation (phonology)PsychologyVisual artsArtComputer sciencePsychotherapistPedagogyAnthropologyPhilosophy

Abstract

fetched live from OpenAlex

This paper examines and compares assimilation and multiculturalism. Although we, as art therapists, might in theory be inclined to embrace multiculturalism over assimilation, when it comes to practice in our art rooms, we find difficulties. This paper will clarify some of these difficulties, the foundations of cultural conflict, so that we may better understand and begin dismantling the barriers which hinder our ability to embrace variety and differences in the art room. Finally, this paper makes the suggestion that we go beyond removing that which hinders us and actively use our very natures as artists to help us embrace diversity, that nature which understands the value of a variety of tools and mediums, the joy of mixing varied textures, colors, shades, and line quality in our work. This is the lesson to be found in every art room and it is within reach of everyone who enters that 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)0.007
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0150.014
Scholarly communication0.0120.007
Open science0.0020.023
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0110.001

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 head0.045
GPT teacher head0.322
Teacher spread0.277 · 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 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

Citations8
Published2000
Admission routes1
Has abstractyes

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