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Record W2743655468 · doi:10.1080/15350770.2017.1330056

Examining the Benefits of Intergenerational Volunteering in Long-Term Care: A Review of the Literature

2017· review· en· W2743655468 on OpenAlexafffund
S. Blais, Lynn McCleary, Linda Garcia, Annie Robitaille

Bibliographic record

VenueJournal of Intergenerational Relationships · 2017
Typereview
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of OttawaBrock University
FundersHealth CanadaBrock UniversityU.S. Department of Labor
KeywordsPsychologyLong-term careGerontologyTerm (time)Developmental psychologyMedical educationMedicinePsychiatry

Abstract

fetched live from OpenAlex

This review examines the benefits of intergenerational interactions between youth volunteers and residents of long-term care homes. Five articles met the criteria for review. Benefits for youth included developing new communication and career-related skills, improved attitudes toward older adults, and the development of meaningful relationships and friendships. Benefits for residents were engagement in activities with the students, enhanced well-being and, for residents with aphasia, improved communication abilities. Further research is needed to evaluate the impact of intergenerational volunteer programs, especially for secondary students as volunteers.

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)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.198
GPT teacher head0.439
Teacher spread0.240 · 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 designSystematic review
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

Citations44
Published2017
Admission routes2
Has abstractyes

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