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Record W2057015047 · doi:10.5430/jnep.v3n3p35

Transformative learning in nursing students through a service learning project with a vulnerable community

2012· article· en· W2057015047 on OpenAlexvenueno aff
Amanda S. Eymard, Pamela Breaux, Kimberly Dozar

Bibliographic record

VenueJournal of Nursing Education and Practice · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsnot available
Fundersnot available
KeywordsTransformative learningService-learningNursingPovertyPopulationEmpathyPsychologyNurse educationHealth promotionMedical educationMedicinePedagogyPublic healthPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

Transformative learning is the phrase used by the authors to describe nursing students’ learning that occurred during a service learning project. Nursing faculty and nursing students visited a population of impoverished children in an after school program and provided education regarding health promotion and injury prevention. Students designed teaching plans regarding topics identified in a needs assessment: (1) injury prevention related to safety, (2) nutrition, (3) physical fitness, (4) health, and (5) bullying. A qualitative analysis of student journals was completed. The students viewed themselves as change agents, and reflected on their stereotypes, and prejudices regarding children living in poverty, and caring for this population.

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)0.010
metaresearch head score (Gemma)0.011
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 score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0150.007
Scholarly communication0.0050.003
Open science0.0030.014
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0050.001

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 head0.154
GPT teacher head0.499
Teacher spread0.345 · 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

Citations18
Published2012
Admission routes1
Has abstractyes

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