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Record W2023940667 · doi:10.5860/crl.75.5.684

Don’t Fear the Reader: Librarian versus Interlibrary Loan Patron-Driven Acquisition of Print Books at an Academic Library by Relative Collecting Level and by Library of Congress Classes and Subclasses

2014· article· en· W2023940667 on OpenAlexfundno aff
David C. Tyler, Joyce C. Melvin, MaryLou Epp, Anita M. Kreps

Bibliographic record

VenueCollege & Research Libraries · 2014
Typearticle
Languageen
FieldComputer Science
TopicLibrary Collection Development and Digital Resources
Canadian institutionsnot available
FundersUniversity of North Carolina at Chapel HillRoyal Roads UniversityNorth Carolina State UniversityUniversity of RochesterWestern Michigan University
KeywordsInterlibrary loanPurchasingAcademic librarySubject (documents)Class (philosophy)Library scienceComputer scienceLibrary instructionLoanWorld Wide WebBusinessSociologyInformation literacyMarketing

Abstract

fetched live from OpenAlex

Recently, a great deal of literature on patron-driven acquisition (PDA) has been published that addresses the implementation and results of PDA programs at academic libraries. However, despite widespread worries that PDA will lead to unbalanced collections, little attention has been paid to whether patrons’ and librarians’ purchasing differ significantly. This study analyzes librarians’ and PDA patrons’ acquisitions at an academic library by relative collecting level and by subject (that is, Library of Congress class and subclass) to determine whether concern over patrons’ collecting are warranted.

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)0.005
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.996
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.003
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.001

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 head0.059
GPT teacher head0.288
Teacher spread0.229 · 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".

Quick stats

Citations12
Published2014
Admission routes1
Has abstractyes

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