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Record W2080866309 · doi:10.1108/02641610810878585

eBook Loans: an e‐twist on a classic interlending service

2008· article· en· W2080866309 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInterlending & Document Supply · 2008
Typearticle
Languageen
FieldComputer Science
TopicLibrary Collection Development and Digital Resources
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsContext (archaeology)Service (business)Interlibrary loanLoanOriginalityWorld Wide WebBusinessDigital libraryComputer sciencePublic relationsKnowledge managementMarketingSociologyPolitical scienceFinance

Abstract

fetched live from OpenAlex

Purpose In April 2007, the Canada Institute for Scientific and Technical Information (CISTI), in collaboration with Ingram MyiLibrary, launched the eBook Loan Service. The paper describes the management of challenges associated with the project as well as the background and context of the aims to eBook Loan Service model. Conclusions and future activities by the partners with regard to e‐book lending are discussed. Design/methodology/approach The paper addresses two main topics: how the eBook Loan Service model was developed, the challenges and risks, the outcomes and benefits; and to evaluate whether a project stretching across boundaries of geography and time as well as between public and commercial partners can be managed successfully. Through a literature review, the context of the e‐book lending model for libraries is addressed, as well as the challenges of virtual project management. Findings The challenges and risks associated with implementing the new service were resolved and the project was a success. Originality/value The new service delivered by this project underlines the richness of new ideas emerging in the library community to improve access to scholarly literature in the digital age. With this model of affordable short‐term access to scholarly e‐books, libraries will be in a better position to serve the just‐in‐time needs of users in the electronic environment and end‐users will have better access.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.706
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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.004
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.027
GPT teacher head0.244
Teacher spread0.217 · 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