MétaCan
Menu
Back to cohort
Record W2995796853 · doi:10.18438/eblip29613

Connecting Users to Articles: An Analysis of the Impact of Article Level Linking on Journal Use Statistics

2019· article· en· W2995796853 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEvidence Based Library and Information Practice · 2019
Typearticle
Languageen
FieldComputer Science
TopicLibrary Collection Development and Digital Resources
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsRanking (information retrieval)VendorComputer scienceLibrary scienceCollection developmentNegative binomial distributionImpact factorStatisticsInformation retrievalBusinessPolitical scienceMarketingPoisson distributionMathematics

Abstract

fetched live from OpenAlex

Abstract
 Objective – Electronic resource management challenges and “big deal” cancellations at one Canadian university library contributed to a situation where a number of electronic journal subscriptions at the university’s health sciences library lacked article level linking. The aim of this study was to compare the usage of journals with article level linking enabled to journals where only journal level linking was available or enabled.
 Methods – A list of electronic journal title subscriptions was generated from vendor and subscription agent invoices. Journal titles were eligible for inclusion if the subscription was available throughout 2018 on the publisher’s platform, if the subscription costs were fully funded by the health sciences library, and if management of the subscription required title-by-title intervention by library staff. Of the 356 journal titles considered, 302 were included in the study. Negative binomial regression was performed to determine the effect of journal vs. article level linking on total COUNTER Journal Report 1 (JR1) successful full-text article requests for 2018, controlling for journal publisher, subject area, journal ranking, and alternate aggregator access.
 Results – The negative binomial regression model demonstrated that article level linking had a significant, positive effect on total 2018 JR1 (coef: 0.645; p < 0.001). Article level linking increased the expected total JR1 by 90.7% when compared to journals where article level linking was not available or enabled. Differences in predicted usage between journals with article level linking and those without article level linking remained significant at various journal ranking levels. This suggests that usage of both smaller, more specialized journals (e.g., Journal of Vascular Research) and larger, general journals (e.g., New England Journal of Medicine) increases when article level linking is enabled.
 Conclusions – This study provides statistical evidence that enabling article level linking has a positive impact on journal usage at one academic health sciences library. Although further study is needed, academic libraries should consider enabling article level linking wherever possible in order to facilitate user access, maximize the value of journal subscriptions, and improve convenience for users.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0010.174
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 head0.036
GPT teacher head0.280
Teacher spread0.244 · 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