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Record W2031206435 · doi:10.2202/1548-923x.2041

Service Learning with Vulnerable Populations: Review of the Literature

2010· review· en· W2031206435 on OpenAlexaff
Angela Gillis, Marian Mac Lellan

Bibliographic record

VenueInternational Journal of Nursing Education Scholarship · 2010
Typereview
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsService-learningService (business)Nurse educationNursingIdentification (biology)SociologyPublic relationsPsychologyMedical educationPedagogyMedicinePolitical scienceBusiness

Abstract

fetched live from OpenAlex

The service learning model has been touted as a powerful pedagogical approach, a reasonable option for providing care to vulnerable and diverse populations, and a vehicle for educating nursing students to become agents of social change. The literature on service learning with vulnerable populations in nursing education is reviewed and synthesized in this article. A description of service learning experiences, identification of knowledge and skills learned, opportunities for critical thinking and reflection, and a discussion of factors that act as enablers and barriers to service learning are explored. Recommendations for successful integration of service learning into educational settings are provided for nurse educators, academic institutions and community partners. As the service learning model spreads across nursing education it is suggested that it offers promise to foster social change and produce graduates who are fully engaged citizens and professionals.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.009
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.163
GPT teacher head0.494
Teacher spread0.331 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations85
Published2010
Admission routes1
Has abstractyes

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