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Record W2781957072

Revisiting the Retrospective: Authorship and Authority in The Michael Snow Project

2015· dissertation· en· W2781957072 on OpenAlexaffabout

Bibliographic record

VenueOCAD University Open Research Repository (OCAD University) · 2015
Typedissertation
Languageen
FieldArts and Humanities
TopicArtistic and Creative Research
Canadian institutionsSchwartz/Reisman Emergency Medicine Institute
Fundersnot available
KeywordsFraming (construction)Argument (complex analysis)Interpretation (philosophy)SociologyEpistemologyAestheticsHistoryArtArchaeologyPhilosophyLinguistics
DOInot available

Abstract

fetched live from OpenAlex

This thesis examines the defining qualities of the retrospective curatorial model using The Michael Snow Project, hosted in 1994 by the Art Gallery of Ontario and The Power Plant, as a case study. A source of modern conceptions of authority, the retrospective employs particular canonization criteria by directing curatorial argument to biographical origins. The occasion of the retrospective therefore imposes a set of interpretive limitations on artworks whose themes problematize authorship, channel elements of chaos or accident, or question historical viewing. A critique of three catalogue essays for the Project demonstrates how—despite curatorial awareness of the retrospective model and various attempts to transcend its structures—these canonization criteria shape interpretation. Both the Project’s critical consciousness of this model and the varied nature of Snow’s corpus present an opportunity to consider the enduring influence of retrospective framing on curatorial discourse, and its continued effects on contemporary deployments of a popular model.

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)0.026
metaresearch head score (Gemma)0.041
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: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0180.053
Scholarly communication0.0160.015
Open science0.0020.010
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.145
GPT teacher head0.368
Teacher spread0.222 · 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

Citations0
Published2015
Admission routes2
Has abstractyes

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