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Record W2024643682 · doi:10.1108/07419051011095863

A unique Twitter use for reference services

2010· article· en· W2024643682 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

VenueLibrary Hi Tech News · 2010
Typearticle
Languageen
FieldComputer Science
TopicWeb and Library Services
Canadian institutionsWomen's and Gender Studies et Recherches FéministesUniversity of British Columbia
Fundersnot available
KeywordsOriginalityWork (physics)Promotion (chess)Service (business)Reference modelTracking (education)Computer scienceValue (mathematics)Reference dataWorld Wide WebLibrary sciencePublic relationsSociologyPolitical scienceBusinessMarketingEngineeringSocial scienceDatabasePolitics

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to illustrate that the personal use of Twitter for tracking reference questions has potential for marketing and promotion of reference work in libraries. Design/methodology/approach The paper provides a brief overview of how Twitter is currently being used in libraries and how it is being used personally by library staff as it relates to reference work. The paper provides an example of how Koerner library at Several University of British Columbia (UBC) is using their institutional Twitter account to “tweet” reference questions asked during public service shifts. Findings Twitter accounts for libraries have the potential to market reference service by bringing attention to how the reference desks are used by the community but also, more broadly, the account can highlight reference as an important role in librarianship. Originality/value The paper offers insight into a non‐traditional form of Twitter use, on an institutional level, in reference work.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.867
Threshold uncertainty score0.851

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 communication0.0010.011
Open science0.0020.001
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 head0.022
GPT teacher head0.235
Teacher spread0.213 · 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