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Record W2068957480 · doi:10.7152/nasko.v4i1.14655

A Space of Transition: Rethinking Surrogates

2013· article· en· W2068957480 on OpenAlexafffund
Hope A. Olson, Lynne C. Howarth

Bibliographic record

VenueNASKO · 2013
Typearticle
Languageen
FieldComputer Science
TopicICT in Developing Communities
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsContext (archaeology)Consistency (knowledge bases)Process (computing)Space (punctuation)Knowledge organizationRepresentation (politics)Interpretation (philosophy)Resource (disambiguation)EpistemologySociologyKnowledge managementComputer sciencePolitical scienceArtificial intelligenceLawHistoryPhilosophy

Abstract

fetched live from OpenAlex

The knowledge organization (KO) process of representing something identifiable typically involves creating a surrogate. The surrogate brings together the thing and the knowledge organization system (KOS). Therefore, we decided to focus on the surrogate and its role in the process of representation. In current practice KOS govern the creation of the surrogate. This something being represented is typically, but not necessarily, an information resource. It may also be artistic, tangible, spiritual, etc., knowledge organization systems meant to organize surrogates that represent something identifiable. A knowledge organization professional (KOP) selects what aspects of the thing to include in the representation. The knowledge organization experts/establishment (KOE) are responsible for the development of the context in which surrogates are created. The KOE are key drivers in determining process, and in developing and maintaining standards. Traditional practices are intended to ensure consistency and uniformity of interpretation and application across a range of physical and digital discourses. This context can be considered anew as postcolonial critic Homi Bhabha’s concept of the Third Space (1994).

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)0.012
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0120.040
Scholarly communication0.0190.035
Open science0.0030.018
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0100.002

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 head0.021
GPT teacher head0.227
Teacher spread0.205 · 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 designTheoretical or conceptual
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

Citations2
Published2013
Admission routes2
Has abstractyes

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Same venueNASKOSame topicICT in Developing CommunitiesFrench-language works237,207