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Record W2060919269 · doi:10.1300/j104v32n02_06

Standardization, Objectivity, and User Focus: A Meta-Analysis of Subject Access Critiques

2001· article· en· W2060919269 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

VenueCataloging & Classification Quarterly · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsObjectivity (philosophy)StandardizationSubject accessSubject (documents)SociologyDiversity (politics)MetadataComputer scienceInformation accessOptimal distinctiveness theoryAdaptation (eye)Knowledge managementWorld Wide WebEpistemologyPsychologySocial psychology

Abstract

fetched live from OpenAlex

ABSTRACT Critiques of subject access standards in LIS literature have addressed biases of gender, sexuality, race, age, ability, ethnicity, language and religion as limits to the representation of diversity and to effective library service for diverse populations. The current study identifies and analyzes this literature as a basis for ameliorating systemic bias and to gather the existing literature for wider accessibility. The study analyzes five quantitative variables: standards discussed, categories of problems, marginalized groups and topics discussed, date, and basis of conclusions (research or experience). Textual analysis reveals that basic tenets of subject access-user-focused cataloguing, objectivity, and standardization-are problematized in the literature and may be the best starting point for future research. In practice, librarians can work to counteract systemic problems in the careful and equitable application of standards and their adaptation to local contexts.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
Threshold uncertainty score0.432

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 studies0.0000.000
Scholarly communication0.0000.003
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 head0.143
GPT teacher head0.394
Teacher spread0.251 · 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