MétaCan
Menu
Back to cohort
Record W2964504562 · doi:10.5430/jnep.v9n10p107

Integration of a community-based engagement model of service learning in a master’s entry nursing program

2019· article· en· W2964504562 on OpenAlexvenueno aff
Kim Amer, Elizabeth Aquino, Jonathan Handrup, Karen Larimer, Young Me Lee, Marisol Morales, Shannon Simatovich

Bibliographic record

VenueJournal of Nursing Education and Practice · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsnot available
Fundersnot available
KeywordsNursingCommunity healthCommunity engagementService (business)Service-learningCommunity nursingPsychologyMedicineMedical educationPedagogyPublic relationsPolitical scienceBusinessPublic health

Abstract

fetched live from OpenAlex

The future of nursing will include a growing presence in communities with less focus on hospital health care. In response to the need for community health focused learning a five-course community engagement experience model was designed for the master’s entry to nursing practice students in a nursing program. Community Engagement, defined as the process of working together in a collaborative spirit with groups of persons who are affiliated by geographic, special interest, or health care needs (CDC/ASTDR, 2006), is an ideal way for nursing students to fully understand the assets and needs of communities and develop goals for the health care concerns of specific communities. The goals of community engagement are to establish trust between clients, agencies, and the School of Nursing, to then develop mutual goals, enlist needed resources and improve learning and health outcomes in the community. This article describes the leveled objectives and course structure for the implementation of the community engagement pedagogy and model.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.381
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.223
GPT teacher head0.466
Teacher spread0.243 · 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 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

Citations5
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Nursing Education and PracticeSame topicService-Learning and Community EngagementFrench-language works237,207