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Record W2974375402 · doi:10.18438/eblip29592

Dewey Decimal Classification Trending Downward in U.S. Academic Libraries, but Unlikely to Disappear Completely

2019· article· en· W2974375402 on OpenAlexaffvenue
Jordan Patterson

Bibliographic record

VenueEvidence Based Library and Information Practice · 2019
Typearticle
Languageen
FieldComputer Science
TopicLibrary Science and Information
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsDewey Decimal ClassificationLibrary of Congress ClassificationDecimalCatalogingClassification schemeLibrary scienceComputer scienceInformation retrievalAcademic libraryLibrary classificationStatisticsMathematicsArithmetic

Abstract

fetched live from OpenAlex

A Review of: Lund, B., & Agbaji, D. (2018). Use of Dewey Decimal Classification by academic libraries in the United States. Cataloging and Classification Quarterly, 56(7), 653-661. https://doi.org/10.1080/01639374.2018.1517851 Abstract Objective – To determine the current use of Dewey Decimal Classification in academic libraries in the United States of America (U.S.). Design – Cross-sectional survey using a systematic sampling method. Setting – Online academic library catalogues in the U.S. Subjects – 3,973 academic library catalogues. Methods – The researchers identified 3,973 academic libraries affiliated with degree-granting post-secondary institutions in the U.S. The researchers searched each library’s online catalogue for 10 terms from a predetermined list. From the results of each search, the researchers selected at least five titles, noted the classification scheme used to classify each title, and coded the library as using Dewey Decimal Classification (DDC), Library of Congress Classification (LCC), both DDC and LCC, or other classification schemes. Based on the results of their data collection, the researchers calculated totals. The totals of this current study’s data collection were compared to statistics on DDC usage from two previous reports, one published in 1975 and one in 1996. The researchers performed statistical analyses to determine if there were any discernible trends from the earliest reported statistics through to the current study. Main Results – Collections classified using DDC were present in 717 libraries (18.9%). Adjusting for the increase in the number of academic libraries in the U.S. between 1975 and 2017, DDC usage in academic libraries has declined by 56% in that time frame. The number of libraries with only DDC in evidence is unreported. Conclusion – The previous four decades have seen a significant decrease in the use of DDC in U.S. academic libraries in favour of LCC; however, the rate at which DDC has disappeared from academic libraries has slowed dramatically since the 1960s. There is no clear indication that DDC will disappear from academic libraries completely.

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)0.014
metaresearch head score (Gemma)0.084
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.982
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.084
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0180.051
Science and technology studies0.0030.004
Scholarly communication0.0110.014
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.003

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 head0.036
GPT teacher head0.273
Teacher spread0.237 · 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.

Study designObservational
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".

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Citations2
Published2019
Admission routes2
Has abstractyes

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