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Record W2964685354 · doi:10.29173/jchla29371

“How Do I Do That?” A Literature Review of Research Data Management Skill Gaps of Canadian Health Sciences Information Professionals

2019· review· en· W2964685354 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of the Canadian Health Libraries Association / Journal de l Association de bilbiothèques de la santé du Canada · 2019
Typereview
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRDMContext (archaeology)Perspective (graphical)Health professionalsKnowledge managementInformation scienceData managementMedical educationPublic relationsLibrary scienceHealth careSociologyMedicineComputer sciencePolitical sciencePedagogyGeography

Abstract

fetched live from OpenAlex

Abstract: There is a recognized need to provide research data management (RDM) services in health sciences libraries. A review of the literature reveals numerous strategies to provide training for health sciences librarians as they provide RDM services to health sciences researchers, faculty, and students. However, no consensus emerges through this literature review with respect to RDM training initiatives. With training initiatives being developed and documented, more in-depth research will emerge that verifies which initiatives have the greatest success for upskilling information professionals in managing research data. This is an area where future library and information studies research can be conducted. It is the hope that with this literature review, I can conduct my own survey to gain more perspective on RDM in a Canadian health sciences library context.

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)0.069
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity
Consensus categoriesMetaresearch, Scholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.146
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0690.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0040.006
Science and technology studies0.0020.000
Scholarly communication0.0090.022
Open science0.0090.001
Research integrity0.0010.003
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 head0.083
GPT teacher head0.413
Teacher spread0.330 · 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