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Record W3107940813 · doi:10.1111/nup.12342

Examining progression and degeneration of nursing science using Imre Lakatos’s methodology of scientific research programs

2020· article· en· W3107940813 on OpenAlexaff
Ahtisham Younas

Bibliographic record

VenueNursing Philosophy · 2020
Typearticle
Languageen
FieldNursing
TopicNursing Diagnosis and Documentation
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsNursing sciencePseudoscienceTransformative learningNursing researchSociology of scientific knowledgeNursing practiceNursingHealth careEpistemologyNursing literaturePsychologyQualitative researchSociologyEngineering ethicsMedicineAlternative medicinePedagogySocial sciencePhilosophyPathology

Abstract

fetched live from OpenAlex

Over the years, nursing research and practice have been through remarkable transformations in response to evolving and emerging healthcare systems and practices. Regarding research, nurses moved beyond merely using the quantitative methodology to combining qualitative, quantitative and mixed methods. In practice, nurses have transitioned from the delivery of medical-based care to nursing theory-guided practice, evidence-based practice, knowledge translation and transformative practice. Some domains of nursing research and practice became progressive, while others degenerated. This paper aims to examine how different domains of nursing research and practice progress and degenerate using Imre Lakatos's methodology of scientific research programs. Lakatos differentiated scientific and pseudoscientific knowledge and coined the idea of scientific research programs. He believed that science in any discipline develops so that some programs are more progressive and others' degenerative. The degeneration and progression of programs occur steadily and rationally and are determined based on the extent of development and programs' potential to predict new solutions to old problems. Adopting this idea could enable nurses to critically analyse research programs in everyday knowledge development to use valid and legitimate programs for informing nursing practice.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.234
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.004
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.563
GPT teacher head0.515
Teacher spread0.048 · 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 teacher head, not a consensus.

Study designBench or experimental
Domainnot available
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

Citations7
Published2020
Admission routes1
Has abstractyes

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