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Record W2559169105 · doi:10.3233/efi-160085

Apps for academic success: Developing digital literacy and awareness to increase usage

2016· article· en· W2559169105 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEducation for Information · 2016
Typearticle
Languageen
FieldComputer Science
TopicWeb and Library Services
Canadian institutionsnot available
Fundersnot available
KeywordsOutreachVendorPromotion (chess)World Wide WebPoint (geometry)Variety (cybernetics)Computer scienceMultimediaMobile technologyMobile deviceInternet privacyBusinessMarketingPolitical science

Abstract

fetched live from OpenAlex

As a consequence of the high adoption levels of mobile technology, users are increasingly accessing academic library-subscribed content via vendor-supplied mobile applications (apps) or responsive websites. However, users may be unaware of the existence of some standalone apps and might miss benefi tting from available apps at their most significant point of need. This paper outlines the McGill Library’s multifaceted approach to promotion and outreach to increase awareness and usage of mobile apps in an effort to provide additional access points for the library’s e-resources. A variety of online and traditional promotional methods were employed, such as faculty news e-bulletins, an app web-guide, images on the Library home page slideshow, and in-person demonstrations, to advertise two of the Library’s subscribed apps, PressReader and BrowZine. Complementing this approach, four different workshops were offered at different times during an academic year targeted to specific audiences: faculty, university communications and library staff, and students. The authors describe the content and results of these initiatives showing how specific promotional strategies appear to have a greater impact on usage. They conclude with thoughts on how current behaviours in mobile usage might begin to affect the future direction of mobile access to library-subscribed e-resources.

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 categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.941
Threshold uncertainty score0.997

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 communication0.0000.017
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 head0.013
GPT teacher head0.287
Teacher spread0.274 · 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