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Record W4233534163 · doi:10.2307/j.ctt6wq4sf.66

An Academic Library’s Efforts to Justify Materials Budget Expenditures

2012· book-chapter· en· W4233534163 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

VenuePurdue University Press eBooks · 2012
Typebook-chapter
Languageen
FieldComputer Science
TopicLibrary Collection Development and Digital Resources
Canadian institutionsPurdue Pharma (Canada)
Fundersnot available
KeywordsAcademic libraryBusinessPolitical scienceComputer scienceLibrary science

Abstract

fetched live from OpenAlex

Academic libraries, like the universities and colleges they serve, are facing increasing pressures to justify budgets and expenditures.Using the business model employed at several other research institutions, the University of Florida (UF) has adopted the accounting system Responsibility Center Management (RCM) which necessitates the university's sixteen colleges to track their individual operational budgets including absorbing a revised tax levied to finance the library.This tax has created a renewed sense of urgency for the library to show details of the material budget expenditures for each college.This paper reveals how staff in the UF Library's Acquisitions Department developed a fresh mapping strategy to track costs of the traditional book budget, print serials, and other tangible materials, but also expenditures for all e-resources drilled down to the individual e-journals purchased through Big Deal packages.Going forward, the library can use this refashioned budget system to reallocate its materials budget to more accurately support the colleges of UF.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.932
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0020.002
Research integrity0.0010.000
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 head0.021
GPT teacher head0.207
Teacher spread0.186 · 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