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Record W4313188993 · doi:10.32920/ihtp.v2i2.1651

Are nurses being heard? The power of Freirean dialogue to transform the nursing profession

2022· article· en· W4313188993 on OpenAlexaffvenue
Idevânia G. Costa

Bibliographic record

VenueInternational Health Trends and Perspectives · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsLakehead University
Fundersnot available
KeywordsNursingDialogicAction (physics)Nurse educationCurriculumHealth carePower (physics)MedicinePsychologyPedagogyPolitical science

Abstract

fetched live from OpenAlex

Nurses need to acquire knowledge about interactive communication, apply critical thinking in prevention and management of illness, and act as patient advocates especially among marginalized and vulnerable populations. This three-pronged approach usually begin during their student years and should include a dialogue framework for use during nursing encounters with patients, family members, and other healthcare providers and for improving the safety and effectiveness of patient care. Therefore, the nursing curriculum should not only include topics related to illness prevention and management, but also prepare nurses to identify and advocate for social justice and health equality by creating a lively and interactive learning environment to allow nurses to build their self-confidence to act and become change agents. Certainly, the COVID-19 pandemic, which exacerbated a nursing shortage and led to limited access to services and poor quality of care for all, underscores the urgency of the Freirean dialogic approach of action-reflection-action. Using this approach, all stakeholders collaborate, discuss, and implement solutions, grow together, and become change agents toward improving nursing care for all.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.933
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.048
GPT teacher head0.420
Teacher spread0.372 · 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 designQualitative
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
Published2022
Admission routes2
Has abstractyes

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