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Record W2121999722 · doi:10.1177/0306312712475256

Legitimate judgment in art, the scientific world reversed? Maintaining critical distance in evaluation

2013· article· en· W2121999722 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSocial Studies of Science · 2013
Typearticle
Languageen
FieldNeuroscience
TopicAesthetic Perception and Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsObjectivity (philosophy)SubjectivityRelativismEpistemologySociologyEpistemic virtueVirtueField (mathematics)NewspaperFoundation (evidence)AestheticsPhilosophyLawPolitical scienceMedia studies

Abstract

fetched live from OpenAlex

This article considers affinities between artistic and scientific evaluations. Objectivity has been widely studied, as it is thought the foundation for legitimate judgments of truth. Yet we know comparatively little about subjectivity apart from its characterization as the obstacle to objective knowledge. In this article, I examine how subjectivity operates as an epistemic virtue in artistic evaluation, which is an especially interesting field for study given the accepted relativism of taste. Data are taken from interviews with 30 book reviewers drawn from major American newspapers including The New York Times, The Los Angeles Times, The Washington Post, and others. The data reveal that critics invest in a set of strategies to effectively ‘objectivize’ the subjectivity intrinsic to artistic evaluation, which I refer to collectively as strategies for maintaining critical distance. I argue that the concrete procedures for producing legitimate judgment in the world of art can be usefully compared to the norms for legitimate judgment in science.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaScience and technology studies
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativehigh
gptMetaresearchScience and technology studies
Domain: Evaluation · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativehigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.398
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.008
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.131
GPT teacher head0.409
Teacher spread0.278 · 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