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Record W2020726632 · doi:10.1108/00220411111145061

The modernity of classification

2011· article· en· W2020726632 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

VenueJournal of Documentation · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiomedical Text Mining and Ontologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsModernityOriginalityFoundation (evidence)MainstreamEpistemologySociologyValue (mathematics)Work (physics)Computer scienceEngineering ethicsData scienceSocial sciencePhilosophyLawPolitical scienceEngineeringMachine learning

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to explore the modernity of current classification theory and work, and outline a foundation for moving classification toward a late‐modern conception. Design/methodology/approach The paper examines the conceptual foundation for current modern classification work, provides critical analysis of that approach, and outlines three conflicts with modernity that shape the path out of the consequences of modernity. Findings The paper presents an understanding of classification that establishes classification on a late‐modern epistemology, and it lays the contours of how to reclaim the intellectual core of classification theory and work. Originality/value The paper establishes a foundation for rethinking classification work, outlines consequences of current mainstream work, and provides concept for developing late‐modern classification theory and practice.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.279
Threshold uncertainty score0.065

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 studies0.0000.000
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 head0.053
GPT teacher head0.311
Teacher spread0.258 · 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