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Record W2534784384 · doi:10.5703/1288284316259

Acquisitions in a Nutshell

2016· article· en· W2534784384 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicLibrary Collection Development and Digital Resources
Canadian institutionsPurdue Pharma (Canada)
Fundersnot available
KeywordsSession (web analytics)Library scienceField (mathematics)Computer scienceManagementPolitical scienceWorld Wide WebEconomics

Abstract

fetched live from OpenAlex

Designed specifically for librarians new to the field of acquisitions, this session featured an informal introduction to the basics of acquisitions librarianship from three standpoints: a veteran acquisitions and serials librarian, a library director with a background in acquisitions, and a librarian who began her first professional appointment in 2013. The session covered a variety of issues related to the acquisition of both monographs and serials in various formats, plus database and backfile purchases. Discussions included definitions, ordering considerations, avoiding purchase of duplicate resources, negotiating prices and access options, licensing, selecting vendors and jobbers, and various services that vendors’ representatives can provide to assist librarians. The presenters discussed various aspects of access versus ownership of e‐books and periodicals and the impact of each on space and budgets both current and future, and suggested the best times in the annual budget cycle for different types of spending decisions.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.881
Threshold uncertainty score0.419

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.007
GPT teacher head0.183
Teacher spread0.176 · 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