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Record W2775922399 · doi:10.18438/b8g66f

Understanding Factors that Encourage Research Productivity for Academic Librarians

2017· article· en· W2775922399 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.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEvidence Based Library and Information Practice · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsUniversity of AlbertaUniversity of WindsorWestern University
FundersCanadian Association of Research LibrariesUniversity of WindsorUniversity of Ottawa
KeywordsProductivityPsychologyUSablePeer reviewComputer sciencePolitical scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Abstract Objective – This project identifies the factors that contribute to the success of librarians as active researchers. Research success is generally aligned with productivity and output, and the authors are therefore interested in understanding the factors that encourage research productivity. This fills a gap in the literature on librarians as researchers, which has tended to focus on barriers rather than enablers. Methods – For this quantitative study, we distributed an online survey to 1,653 potential participants across Canada and received 453 usable responses for a 27% response rate. The survey asked participants to report their research outputs and to answer questions that addressed three categories of factors: Individual Attributes, Peers and Community, and Institutional Structures and Supports. We then statistically analyzed participant responses in order to identify relationships between the research output variables (weighted output score and number of peer-reviewed articles) and the three categories, the factors within those categories, and the constituent components. Results – Participants’ research output consisted largely of presentations, non-peer-reviewed articles, peer-reviewed articles, and posters. All three categories of factors were significantly related to research output, both for a calculated weighted output score and for number of peer-reviewed articles. All of the factors identified within those categories were also significant when tested against weighted output score, but Intrinsic Motivations was not a significant factor when tested against number of peer-reviewed articles. Several components of factors were also not significant for number of peer-reviewed articles. Age was the only significant component of Demographics. Three components of Education and Experience were significant: whether participants had received research training after completing their MLIS, whether they were working on an advanced degree, and the institution where they had obtained their MLIS. Conclusions – Research productivity is significantly impacted by all three categories: Individual Attributes, Peers and Community, and Institutional Structures and Supports. Fostering an environment that focuses on all of these areas will be most likely to promote research output for librarians. At the same time, this study’s findings point to particular aspects that warrant further investigation, such as the nature and effect of institutional support and librarians’ motivations for doing research.

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)0.004
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.001
Scholarly communication0.0050.862
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.345
GPT teacher head0.427
Teacher spread0.082 · 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