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Record W2020513123 · doi:10.3928/0098-9134-20040301-12

Students and Senior Citizens Learning from Each Other

2004· review· en· W2020513123 on OpenAlexaboutno aff
Sally Fusner, Sharon Staib

Bibliographic record

VenueJournal of Gerontological Nursing · 2004
Typereview
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumService-learningInterviewMedical educationObservational studyPsychologyQuarter (Canadian coin)Perspective (graphical)NursingMedicinePedagogyGerontologySociology

Abstract

fetched live from OpenAlex

A service learning experience in a senior citizen center was planned for first-quarter associate-degree nursing students at a university. Activities were planned that would benefit both student learning and senior citizen health and well-being. Students had the opportunity to interact with well elderly adults before dealing with ill or frail elderly adults, thus preventing the formation of some negative attitudes about elderly individuals. Students practiced interviewing, using observational skills and taking blood pressures in a relaxed environment. Benefits to the senior citizens included having their blood pressure checked and learning about home safety and nutrition. Interactions made the senior citizens feel valued. Evaluation of the experience was positive from the students', senior citizens', faculty's, and center director's perspective. As a result, this service learning experience has been incorporated into the nursing curriculum for the university.

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)0.005
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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0010.005
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.164
GPT teacher head0.447
Teacher spread0.283 · 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

Citations21
Published2004
Admission routes1
Has abstractyes

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