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Record W39030002 · doi:10.1016/j.aca.2024.342898

"All Textbooks in the Library!"An Experiment with Library Reserves

2012· article· en· W39030002 on OpenAlexaboutno aff
Tony Greiner

Bibliographic record

VenueAnalytica Chimica Acta · 2012
Typearticle
Languageen
FieldComputer Science
TopicLibrary Collection Development and Digital Resources
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Collection developmentLoanInterlibrary loanAcademic libraryLibrary scienceData collectionBusinessHistoryComputer scienceFinanceSociologySocial scienceArchaeology

Abstract

fetched live from OpenAlex

In the fall of 2010, a grant of $36,000 allowed Portland Community College Library to purchase and place on reserve a copy of every required text at one of its campuses. A smaller college “center” also placed all required texts on reserve. The program was very popular with students and parts of the reserve collection received heavy use. Compared to the previous fall term, overall use of reserves at the Cascade Campus library rose 35%, and the Southeast Center collection saw an increase of 110%. However, use of the collection was unevenly distributed, with 26% of the books having more than 11 uses that quarter, but a troubling number (37%) receiving no checkouts at all. An analysis of the data suggests several ways that books with 11 or more uses per quarter could be increased to over 70%. These are to purchase and process books in a timely manner, to adjust loan periods for some items, or to purchase texts only for courses with multiple sections. Use numbers compiled over the following 8 quarters show that textbooks purchased and placed on reserve will be used for several successive terms. Keywords: Library Reserves, Textbooks, Sustainability, Course Reserves, Community College Libraries.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.455
Threshold uncertainty score0.777

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0050.002
Scholarly communication0.0060.008
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.4550.313

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 head0.026
GPT teacher head0.238
Teacher spread0.211 · 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

Citations7
Published2012
Admission routes1
Has abstractyes

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