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Record W1482357562 · doi:10.5902/217976923705

Humanization of nursing care through academic education

2012· article· en· W1482357562 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmericanae (AECID Library) · 2012
Typearticle
Languageen
FieldMedicine
TopicPalliative and Oncologic Care
Canadian institutionsRegina General Hospital
Fundersnot available
KeywordsWorkloadMetropolitan areaNursingPsychologyHealth careObject (grammar)Descriptive researchProcess (computing)Exploratory researchMedical educationMedicineSociologyComputer sciencePolitical scienceSocial science

Abstract

fetched live from OpenAlex

Objective: to understand how nurses perform humanized care through learning acquired in their academic experience. Method: this is a qualitative study, descriptive exploratory developed with eight nurses from a hospital in the metropolitan area of Porto Alegre/RS. Data were collected through interviews. Results: the results showed two categories of analysis: possibilities of humanization in care, where they were cited communication, reception and workload as factors interfering in the process and humanization in academic, whose memory of the respondents are based on memories of the teacher as a role model. Final Thoughts: it was found that there are still gaps in training on humanization as an object of study in undergraduate courses, so that the human dimensions of care proposals are still so disjointed with the reality of healthcare in the country

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.

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)0.000
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 score0.074
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.045
GPT teacher head0.380
Teacher spread0.335 · 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