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Record W4386139119 · doi:10.56397/as.2023.08.06

Art and Counterculture: Shaping Identity Through Expression and Engagement

2023· article· en· W4386139119 on OpenAlexaff
Donar Rathna

Bibliographic record

VenueArt and Society · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCountercultureAppropriationMainstreamSociologyAestheticsNonconformistExpression (computer science)Context (archaeology)Media studiesPoliticsPolitical scienceEpistemologyArtHistoryLawComputer science

Abstract

fetched live from OpenAlex

This paper explores the dynamic relationship between artistic expression and counterculture, shedding light on how artworks shape, reflect, and convey identities within alternative and nonconformist cultures. Countercultural movements challenge prevailing norms, seeking to establish alternative value systems, and artistic expression becomes a powerful medium through which these identities are both constructed and communicated. Through a historical overview, case studies, and analysis of media representation, the paper examines the intricate interplay between counterculture and art. It also delves into the challenges posed by cultural appropriation, the assimilation of countercultural symbols, and the ongoing struggle to balance authenticity and acceptance. Ultimately, this study seeks to provide a comprehensive understanding of how art serves as a dynamic force in defining and shaping countercultural identities within the context of mainstream society.

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)0.006
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: none
Teacher disagreement score0.015
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0050.025
Scholarly communication0.0150.008
Open science0.0010.014
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.098
GPT teacher head0.331
Teacher spread0.233 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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