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Analysis of the particularities of Lusophone participation in a Nursing Knowledge Network

2023· article· en· W4321216711 on OpenAlexaff
Margareth Santos Zanchetta, Marcelo Medeiros, José Carlos Carvalho, Cristina Lavareda Baixinho, Cândida Çaniçali Primo, Manuel Chaves, Márcia Teles de Oliveira Gouvéia, Nara Marilene Oliveira Girardon-Perlini, Cristianne Maria Famer Rocha, Edwaldo Costa, Walterlânia Silva Santos, Vera Lúcia Mendes de Paula Pessoa

Bibliographic record

VenueEscola Anna Nery · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsOriginalityCreativityDisseminationWork (physics)InternationalizationKnowledge managementAction (physics)SociologyNursingPsychologyMedicinePolitical scienceComputer scienceBusinessEngineering

Abstract

fetched live from OpenAlex

Abstract Objective To describe the conceptual exercise of reflecting on the possibilities and particularities of the participation of Lusophone schools of nursing in the Nursing Knowledge Network. Method An analysis was conducted using information obtained from an environmental scan of institutional resources following the conceptual framework by Prug and Prusak on the knowledge networks. The learnings reported in the analysis are based on the collected information and reflections on the positive and negative aspects of participation, while proposing possible solutions for an action plan. Results There is interest in the internationalization of research and collaborative work both as institutional actions to support nursing research and potential benefits due to participation in the Network. The collaborative work has potential to increase the impact of research, expedite dissemination and use of results both in education and in clinical practice, broadening the horizons of Lusophone nursing science. Conclusion and Implications for practice Participation of these institutions in the Network offers numerous possibilities to demonstrate the originality, creativity and expertise of their teaching and research practice, encouraging the sharing of ideas and practices. The practice of scientific production in all its scenarios by educators and students can be improved through refined ways of thinking, creating, producing, and disseminating 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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.408

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.005
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.065
GPT teacher head0.471
Teacher spread0.406 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2023
Admission routes1
Has abstractyes

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