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Record W2093983606 · doi:10.1108/03074801011089314

Once you get them, how do you keep them? Millennial librarians at work

2010· article· en· W2093983606 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

VenueNew Library World · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsOriginalityRelevance (law)Work (physics)Value (mathematics)Administration (probate law)SociologyPublic relationsRelation (database)Library sciencePolitical scienceComputer scienceEngineeringSocial scienceQualitative research

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to draw attention to the unique characteristics of Millennial librarians. These characteristics are related to larger issues having current and future relevance to Millennial librarians, colleagues of other generations, as well as library administration. Design/methodology/approach The paper explores training, leadership and work‐life balance in relation to Millennial librarians. Findings Certain defining characteristics of the Millennial generation need to be recognized and discussed by library administration and librarians of all generations. Practical implications Surveying the literature related to Millennial librarians' possible implications can assist in creating increased awareness of this group. Originality/value Much research focuses on engaging and teaching Millennials as library users. Infrequently discussed, however, is the concept of Millennials as librarians and the paper attempts to fill this gap.

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, Insufficient payload (model declined to judge)
Consensus categoriesScholarly communication, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.304
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
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0020.041
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0310.002

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 head0.021
GPT teacher head0.237
Teacher spread0.217 · 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