MétaCan
Menu
Back to cohort
Record W3088994392 · doi:10.1017/s0714980820000318

Social Participation in Long-term Residential Care: Case Studies from Canada, Norway, and Germany

2020· article· en· W3088994392 on OpenAlexaffabout
Ruth Lowndes, James Struthers, Gudmund Ågotnes

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2020
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsTrent UniversityYork University
Fundersnot available
KeywordsStaffingFlexibility (engineering)Multidisciplinary approachEveryday lifeWork (physics)Long-term carePublic relationsNursingQuality of life (healthcare)EthnographyPsychologySociologyBusinessPolitical scienceMedicineManagement

Abstract

fetched live from OpenAlex

Meaningful social engagement in everyday activities can enhance resident quality of life in nursing homes. In this article, we draw on data collected in a multidisciplinary, international study exploring promising practices in long-term care homes across Canada, Norway, and Germany, to investigate conditions that either allow for or create barriers to residents' social participation. Within a feminist political economy framework using a team-based rapid ethnography approach, observations and in-depth interviews were conducted with management, staff, volunteers, students, families, and residents. We argue that the conditions of work are the conditions of care. Such conditions as care home location, building layout, staffing levels, and work organization, as well as governing regulations, influence if and how residents can and do engage in meaningful everyday social life in/outside the nursing home. The presence of promising conditions that facilitate resident social participation, particularly those promoting flexibility and choice for residents, directly impacts their overall health and well-being.

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)0.004
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.384

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.005
Science and technology studies0.0180.009
Scholarly communication0.0040.001
Open science0.0020.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.334
Teacher spread0.300 · 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

Citations32
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicGeriatric Care and Nursing HomesFrench-language works237,207