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Record W2947810104 · doi:10.33137/cjal-rcbu.v5.30417

Conceptions of Research Among Academic Librarians and Archivists

2019· article· en· W2947810104 on OpenAlexaffvenueabout
Lise Doucette, Kristin Hoffmann

Bibliographic record

VenueCanadian Journal of Academic Librarianship · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicDigital and Traditional Archives Management
Canadian institutionsWestern UniversityUniversity of Toronto
Fundersnot available
KeywordsSociologyProcess (computing)Library sciencePsychologyPedagogyComputer science

Abstract

fetched live from OpenAlex

Academic librarians and archivists occupy a unique role as researchers and as practitioners who support faculty and student researchers. However, the ways in which librarians and archivists think about research is largely unexamined, while faculty conceptions of research have been studied extensively. In this study, we analyzed drawings and interviews of 25 Canadian academic librarians and archivists and identified six conceptions of research: research is a shared, community experience; research leads to learning and growth; research is influenced by personal and professional experience; research is a process involving interrelated components; research involves refining and answering a question; research by librarians and archivists is not “real” research. Our analysis also shows that librarians and archivists experience research in much the same way as faculty researchers. These findings represent a new understanding of librarians and archivists as researchers, and are a contribution to the literature on conceptions of research more broadly. The six conceptions of research will help librarians and archivists think in new ways about their roles as researchers and as practitioners.

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)0.119
metaresearch head score (Gemma)0.099
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.933
Threshold uncertainty score0.631

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1190.099
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0260.017
Science and technology studies0.0310.169
Scholarly communication0.0470.021
Open science0.0060.015
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0020.000

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 head0.089
GPT teacher head0.267
Teacher spread0.178 · 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.

Study designQualitative
DomainMethods
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".

Quick stats

Citations2
Published2019
Admission routes3
Has abstractyes

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