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Record W2620750768 · doi:10.1108/pmm-05-2017-0022

How Canadian librarians practice and assess individualized research consultations in academic libraries

2017· article· en· W2620750768 on OpenAlexaffabout
Karine Fournier, Lindsey Sikora

Bibliographic record

VenuePerformance Measurement and Metrics · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsDemographicsMedical educationService (business)Computer-assisted web interviewingOrder (exchange)PsychologyMedicineComputer scienceSociologyBusiness

Abstract

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Purpose Though we live in a digital era, libraries offer significant hours of in-person reference services, in combination with online reference services. Nevertheless, an increase in requests for in-person, individualized research consultations (IRCs) over the last few years has been observed. IRCs between librarians and students are common practice in academic institutions. While these sessions can be deemed useful for patrons, as they are tailored to their specific needs, however, they can also be time consuming for the librarians. Therefore, it is important to evaluate this service, and assess its impact in order to ensure that the users are getting the most out of their sessions. The purpose of this paper is to gather information on the evaluation and assessment tools that Canadian institutions are using to obtain feedback, measure their impact and improve their consultation services. Design/methodology/approach A bilingual (French and English) web-based questionnaire was issued, with a generic definition of IRCs provided. The questionnaire included general demographics and background information on IRC practices among Canadian academic librarians, followed by reflective questions on the assessment process of such practices. The questionnaire was sent to Canadian academic librarians via e-mail, using professional librarian associations’ listservs, and Twitter was used for dissemination as well. Findings Major findings of the survey concluded that the disciplines of health sciences and medicine, as well as the arts and humanities are the heaviest users of the IRC service model. On average, these sessions are one hour in length, provided by librarians who often require advanced preparation time to adequately help the user, with infrequent follow-up appointments. It was not surprising that a lack of assessment methods for IRCs was identified among Canadian academic libraries. Most libraries have either no assessment in place for IRCs, or they rely heavily on informal feedback from users, comments from faculty members and so on. A small portion of libraries use usage statistics to assess their IRCs service, but other means of assessment are practically non-existent. Research limitations/implications The survey conducted was only distributed to Canadian academic libraries. Institutions across the USA and other countries that also perform IRCs may have methods for evaluating and assessing these sessions which the authors did not gather; therefore, the evidence is biased. As well, each discipline approaches IRCs very differently; therefore, it is challenging to compare the evaluation and assessment methods between each discipline. Furthermore, the study’s population is unknown, as the authors did not know the exact number of librarians or library staff providing IRCs by appointment in academic Canadian institution. While the response rate was reasonably good, it is impossible to know if the sample is representative of the population. Also, it needs to be acknowledged that the study is exploratory in nature as this is the first study solely dedicated at examining academic librarians’ IRC practices. Further research is needed. As future research is needed to evaluate and assess IRCs with an evidence-based approach, the authors will be conducting a pre-test and post-test to assess the impact of IRC on students’ search techniques. Originality/value Evidence-based practice for IRCs is limited. Very few studies have been conducted examining the evaluation and assessment methods of these sessions; therefore, it was believed that a “lay of the land,” so to speak, was needed. The study is exploratory in nature, as this is the first study solely dedicated at examining the evaluation and assessment methods of academic librarians’ IRC practices.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.028
metaresearch head score (Gemma)0.080
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.902
Threshold uncertainty score0.709

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.080
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.014
Science and technology studies0.0150.004
Scholarly communication0.0120.004
Open science0.0030.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.656
GPT teacher head0.551
Teacher spread0.105 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations10
Published2017
Admission routes2
Has abstractyes

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