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NURSE LEADERSHIP PRACTICES IN PRIMARY HEALTH CARE: A GROUNDED THEORY

2016· article· en· W2534813318 on OpenAlexaff
Gabriela Marcellino de Melo Lanzoni, Betina Hörner Schlindwein Meirelles, Greta G. Cummings

Bibliographic record

VenueTexto & Contexto - Enfermagem · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGrounded theoryNursingQualitative researchMeaning (existential)Health careContext (archaeology)Work (physics)MedicinePsychologySociologyPolitical science

Abstract

fetched live from OpenAlex

ABSTRACT This is a qualitative study and its aim was to understand the meaning of nurse leadership exercised in the services of Primary Health Care in a municipality located in Southern Region of Brazil. Grounded Theory was used as methodological framework. Data collection was carried out with semi-structured interviews applied to 30 nurses who worked in Primary Health Care and nursing professors, divided into four groups, between 2011 and 2012. After the analysis process, nine categories emerged and sustained the phenomenon 'Revealing the nursing leadership practices in the complex context of Primary Health Care'. Leadership was understood as a resource in the process of caring/managing people and developing a team of leaders, intending the organization and qualification of health work. It is important to rescue the clinical work of nurses, in order to keep their investment in the health team and to strengthen the binomial leader/caregiver.

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)0.019
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0040.007
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.623
GPT teacher head0.573
Teacher spread0.050 · 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 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

Citations27
Published2016
Admission routes1
Has abstractyes

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