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Record W3214476324 · doi:10.32920/ryerson.14664342.v1

Legibility in the liminal: challenging the symbolic order, an exhibition of drawing

2021· preprint· en· W3214476324 on OpenAlexaff
Joseph Frederick Laevens

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicMedia, Communication, and Education
Canadian institutionsToronto Metropolitan UniversityARC Resources (Canada)York University
Fundersnot available
KeywordsExplicationReinterpretationObject (grammar)Simple (philosophy)Meaning (existential)Computer scienceStudioOrder (exchange)LinguisticsSketchExhibitionAestheticsVisual artsEpistemologyArtArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

"Amidst the 'Glossary of Commonly Misused Words' in the Writers Digest Grammar Desk Reference, the adverb hopefully is demonstrated in its proper usage with a fortune cookie message that reads: 'It is sometimes better to travel hopefully than to arrive'. (Lutz, 332) This paper takes its character from a similar elaboration from within its purpose. In the most simple way, that purpose is to formulate a critical explanation of the studio works as surveyed and documented. As explication, it imbues its meaning as a manner of traveling hopefully upon the arrival of the action of the project. This might seem simple enough but in order to contextualize both the studio works and the explication the reader will be required to play the double game of both conceptually traveling and perceptually arriving. Though it may seem arbitrary, there is no other way any higher possibility of agreement between text and object could be arranged. To argue on behalf of the studio works would prioritize perceptual arrival over the viewer's experience and to realize art about theories is easily a misuse of the word hopeful"--From the introduction, page 3.

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)0.002
metaresearch head score (Gemma)0.005
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: Other · Consensus signal: Other
Teacher disagreement score0.012
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.026
Scholarly communication0.0120.008
Open science0.0010.006
Research integrity0.0020.003
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 head0.114
GPT teacher head0.395
Teacher spread0.281 · 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
GenreOther

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
Published2021
Admission routes1
Has abstractyes

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Same topicMedia, Communication, and EducationFrench-language works237,207