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Record W4296789810 · doi:10.18438/eblip30129

What Do Reference Librarians Do Now?

2022· article· en· W4296789810 on OpenAlexvenueno aff
Monty L. McAdoo

Bibliographic record

VenueEvidence Based Library and Information Practice · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsDatabase transactionValue (mathematics)Work (physics)InstitutionMedical educationPsychologyComputer sciencePublic relationsKnowledge managementLibrary scienceSociologyPolitical scienceMedicine

Abstract

fetched live from OpenAlex

Objective - The primary purpose of this study was to better understand the nature of “reference” and reference transactions. Methods - This study looked at four years’ of reference transaction (RT) data recorded at a small, state-owned university. Results - The data clearly indicates that the overall number of RT continues to decline. It also reveals that, despite the use of student mentors, librarians are still involved with a majority of RT, regardless of whether or not they require the expertise of a librarian to resolve. Conclusion - Continuing to be involved with RT which do not require the knowledge or training of a librarian (e.g., directional) can have a diminutive effect on the perceived role, work, and value of librarians. As such, it is suggested that these sorts of questions be addressed by student mentors or staff members. In turn, this will allow librarians to focus on those questions and activities which do require their unique knowledge and skills. Along similar lines, it is also suggested that librarians explore and identify new, non-traditional ways of applying their expertise to student success initiatives and the overall academic life of the institution. With the merger of three libraries, data from this study has been and continues to be used to make informed decisions about the provision of reference services in a new, integrated library environment.

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.

How this classification was reachedexpand

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.938
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0050.897
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.000

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 head0.023
GPT teacher head0.290
Teacher spread0.266 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2022
Admission routes1
Has abstractyes

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