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Record W4401117100 · doi:10.5206/elip.v6i1.16783

Casting a Wider Net: Podcasts to Promote Reading for Library Users

2024· article· en· W4401117100 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.

Bibliographic record

VenueEmerging Library & Information Perspectives · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicRadio, Podcasts, and Digital Media
Canadian institutionsWestern University
Fundersnot available
KeywordsReading (process)PopularityActive listeningAppealWorld Wide WebStyle (visual arts)ClubComputer scienceLibrary scienceMultimediaSociologyPsychologyPolitical scienceVisual artsArt

Abstract

fetched live from OpenAlex

The article examines the growing role of podcasts in readers' advisory services, emphasizing their potential to engage users with literature and foster a love of reading. As podcasts gain popularity, particularly among younger audiences, they present a unique opportunity for librarians to recommend nonfiction podcasts about books and reading. Unlike audiobooks, podcasts offer shorter, more accessible listening experiences that can introduce users to new titles, support leisure reading, and create a sense of community. The article explores various podcast formats, including book recommendation shows, book club-style discussions, and deep dives into individual books, highlighting their appeal and utility. It argues for integrating podcast recommendations into librarians' practices to enrich the readers' advisory process and connect patrons with literature in innovative ways.

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 categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.827
Threshold uncertainty score0.999

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 studies0.0010.000
Scholarly communication0.0020.031
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 head0.015
GPT teacher head0.287
Teacher spread0.272 · 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