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Record W2064744341 · doi:10.1108/ilds-02-2014-0019

In a world of Amazon, is it time to rethink ILL?

2014· article· en· W2064744341 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

VenueInterlending & Document Supply · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinTech, Crowdfunding, Digital Finance
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInterlibrary loanPurchasingRentingOriginalityValue (mathematics)BusinessMarketingOperations researchComputer sciencePolitical scienceWorld Wide WebSociologyEngineeringLawSocial scienceQualitative research

Abstract

fetched live from OpenAlex

Purpose – This paper aims to evaluate the use of alternative methods compared to traditional interlibrary loan (ILL) processes. Design/methodology/approach – ILL departments around the world were surveyed about their policies and procedures for obtaining materials for their users. Findings – The survey results indicated that alternative methods are predominantly a fringe activity, while most materials are still obtained through traditional ILL processes. There continues to be a great deal of room for exploration of purchasing, renting and the use of free resources to fill ILL requests. Originality/value – This article shows that there continues to be a great deal of room for exploration of purchasing, renting and the use of free resources to fill ILL requests.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.007

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 head0.010
GPT teacher head0.244
Teacher spread0.234 · 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