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Record W1845841479 · doi:10.18438/b8h59j

Persuasive Evidence: Improving Customer Service through Evidence Based Librarianship

2006· article· en· W1845841479 on OpenAlexvenueno aff
Wendy Abbott

Bibliographic record

VenueEvidence Based Library and Information Practice · 2006
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsnot available
Fundersnot available
KeywordsService (business)Process (computing)Action researchProject managementCochrane LibraryKnowledge managementService delivery frameworkComputer scienceMedical educationPublic relationsBusinessPsychologyManagementMedicineMarketingPolitical sciencePedagogyMEDLINE

Abstract

fetched live from OpenAlex

Objective - To demonstrate how evidence based practice has contributed to informing decisions and resolving issues of concern in service delivery at Bond University Library. 
 
 Methods - The paper critically analyses three evidence based research projects conducted at Bond University Library. Each project combined a range of research methods including surveys, literature reviews and the analysis of internal performance data to find solutions to problems in Library service delivery. The first research project investigated library opening hours and the feasibility of twenty-four hour opening. Another project researched questions about the management of a collection of feature films on DVD and video. The third project investigated issues surrounding the teaching of EndNote to undergraduate students. 
 
 Results - Despite some deficiencies in the methodologies used, each evidence based research project had positive outcomes. One of the highlights and an essential feature of the process at Bond University Library was the involvement of stakeholders. The ability to build consensus and agree action plans with stakeholders was an important outcome of that process.
 
 Conclusion - Drawing on the experience of these research projects, the paper illustrates the benefits of evidence based information practice to stimulate innovation and improve library services. Librarians, like most professionals, need to continue to develop the skills and a culture to effectively carry out evidence based practice.

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)0.004
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.477
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.000
Scholarly communication0.0010.441
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.108
GPT teacher head0.419
Teacher spread0.311 · 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

Citations8
Published2006
Admission routes1
Has abstractyes

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