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Record W2161041115 · doi:10.1002/asi.21635

Complex concepts into basic concepts

2011· article· en· W2161041115 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 the American Society for Information Science and Technology · 2011
Typearticle
Languageen
FieldComputer Science
TopicSemantic Web and Ontologies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordssortComputer scienceEpistemologyDisciplineSubject (documents)Set (abstract data type)Key (lock)SociologyObstacleCognitive scienceData sciencePsychologySocial scienceWorld Wide WebInformation retrieval

Abstract

fetched live from OpenAlex

Abstract Interdisciplinary communication, and thus the rate of progress in scholarly understanding, would be greatly enhanced if scholars had access to a universal classification of documents or ideas not grounded in particular disciplines or cultures. Such a classification is feasible if complex concepts can be understood as some combination of more basic concepts. There appear to be five main types of concept theory in the philosophical literature. Each provides some support for the idea of breaking complex into basic concepts that can be understood across disciplines or cultures, but each has detractors. None of these criticisms represents a substantive obstacle to breaking complex concepts into basic concepts within information science. Can we take the subject entries in existing universal but discipline‐based classifications, and break these into a set of more basic concepts that can be applied across disciplinary classes? The author performs this sort of analysis for Dewey classes 300 to 339.9. This analysis will serve to identify the sort of ‘basic concepts’ that would lie at the heart of a truly universal classification. There are two key types of basic concept: the things we study (individuals, rocks, trees), and the relationships among these (talking, moving, paying).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.003
Scholarly communication0.0000.002
Open science0.0020.000
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 head0.033
GPT teacher head0.310
Teacher spread0.277 · 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