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Record W4396821859 · doi:10.54481/intertext.2023.2.10

Enquiring for Expressing Identity within Art Courses in Conventional Classes from the Diversity and Inclusion Perspective

2024· article· en· W4396821859 on OpenAlexaff
Lucie Russbach

Bibliographic record

VenueIntertext · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsInclusion (mineral)Perspective (graphical)Diversity (politics)Identity (music)SociologyGender studiesAestheticsAnthropologyArtVisual arts

Abstract

fetched live from OpenAlex

The multiplication of identity defining spaces in our globalized and technological society can generate tensions for individuals who are in a situation of negotiating, in different contexts, multiple identities that are sometimes perceived as incompatible (Beauregard, 2019). Indeed, each individual has several identities - these being flexible and evolving -, being at the intersection of several types of diversity, even if he is the only representative of his "category" (Ginzburg, 2003). These identities are expressed differently in the different spheres of his work and life, including school, and in each of the school subjects, including the arts. This text aims to discuss - in the context of the visual arts - the expression of identity from a perspective of diversity and inclusion. Therefore, the articulation and adaptation to the context of individual identities will be addressed, and especially the interactions between individual and social identity (Descombes, 2017). The fine arts discipline is examined as a privileged terrain of expression (Lemonchois, 2011) and sharing of sensitive experience (Rancière, 2000). How can this space of intersubjective dialogue lead to better understanding between individuals, to greater inclusion of individual diversity and multiple identities, and ultimately to an improvement in coexistence? These are the aspects mainly explored in this article.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.388
Teacher spread0.336 · 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 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
Published2024
Admission routes1
Has abstractyes

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