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Communication of Research and Practice Knowledge in Nursing Literature

2000· article· en· W2022056011 on OpenAlexaboutno aff
Ann L. O'Neill, Margery Duffey

Bibliographic record

VenueNursing Research · 2000
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsnot available
Fundersnot available
KeywordsNursingNursing researchNursing practicePsychologyMedicineKnowledge managementComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Previous research did not indicate whether communication occurred between the research and practice components of nursing knowledge. OBJECTIVES: This study was designed to examine the extent of communication between or within the nursing-research and nursing-practice components of the nursing literature. METHODS: Specific citing/cited relationships from the Current Index to Nursing and Allied Health Literature (CINAHL) are analyzed using citation analysis. The sample was taken from the population of indexed documents that contained references, that had the subject code of nursing, and that were originally published in the United States or Canada in 1989. RESULTS: The results show that authors of research articles tend to cite research articles more often than practice articles, and that authors of practice articles tend to cite practice articles more often than research articles. Authors with research degrees publish research articles more often than would be expected by chance, and authors with clinical and undergraduate degrees publish practice articles more often than expected. Authors associated with research institutions tend to publish research articles, and those affiliated with service institutions tend to publish practice articles. Most cited documents (69.4%) are from disciplines other than nursing. CONCLUSIONS: The existence of communication between the research and the practice component of nursing knowledge was demonstrated and appears to be more prevalent than previously indicated. Further research on how the cited literature is used would enable us to know about the depth and quality of the communication event and to note variations as the body of nursing knowledge evolves.

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)0.071
metaresearch head score (Gemma)0.383
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.986
Threshold uncertainty score0.376

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0710.383
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0170.019
Science and technology studies0.0030.007
Scholarly communication0.0140.013
Open science0.0020.008
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.429
GPT teacher head0.712
Teacher spread0.283 · 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 designObservational
DomainReporting
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

Citations28
Published2000
Admission routes1
Has abstractyes

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