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Record W4388832921 · doi:10.1177/10784535231213843

Dialectical Pluralism for Nursing Knowledge Development

2023· review· en· W4388832921 on OpenAlexaff
Shahzad Inayat, Graham McCaffrey

Bibliographic record

VenueCreative Nursing · 2023
Typereview
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDialecticPluralism (philosophy)EpistemologySociologyNursing theoryRelevance (law)PsychologyNursingMedicineMEDLINEPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

The purpose of this paper is to explore the potential of dialectical pluralism (DP) for nursing knowledge development. Nursing scholars have discussed ways of developing nursing knowledge, exploring the fit and relevance of various worldviews for knowledge development and examining the dynamic and perpetual processes of knowledge development. Scholars have argued that knowledge development occurs under a certain worldview to which the researcher adheres. Many nurses employ various worldviews, which can give rise to ontological and epistemological conflicts. DP can help nurses appreciate the diversity of worldviews and recognize the importance of implicit worldviews to generate more practical nursing knowledge. DP as a philosophical approach can enable nurses to communicate between diverse worldviews, become tolerant of conflicting differences, and develop an array of nursing knowledge.

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)0.027
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.027
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.007
Science and technology studies0.0040.028
Scholarly communication0.0120.012
Open science0.0020.011
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0030.001

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 head0.278
GPT teacher head0.534
Teacher spread0.255 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations7
Published2023
Admission routes1
Has abstractyes

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