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Record W2617081748 · doi:10.1177/1363459317708825

Facilitating resident community in nursing homes: a slippery slope? An analysis on collectivistic and individualistic approaches

2017· article· en· W2617081748 on OpenAlexfundaboutno aff
Gudmund Ågotnes, Christine Øye

Bibliographic record

VenueHealth An Interdisciplinary Journal for the Social Study of Health Illness and Medicine · 2017
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsnot available
FundersUniversitetet i BergenYork UniversityHøgskulen på Vestlandet
KeywordsIndividualismCollectivismNursingIdeologyNursing homesPsychologyMedicineSociologyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

Residents in nursing homes are old and frail and are dependent on constant care, medical, or otherwise, by trained professionals. But they are also social beings, secluded in an institutional setting which is both total and foreign. In this setting, most of the residents most of the time must relate to other residents: other residents are the nursing home residents' peers, companions, and perhaps even significant others. In this article, we will discuss how resident communities in nursing homes are influenced by the approaches of nursing home staff. Two nursing homes have been included in this article-one from Canada and one from Norway. Participant observation was conducted at these two nursing homes, predominantly focusing on everyday-life activities. The cases from Norway and Canada are illustrative of two very different general approaches to residents: one collectivistic and one individualistic. These general approaches produce different contexts for the formation and content of resident communities, greatly affecting nursing home residents. The significance of these approaches to resident community is profound and also somewhat unanticipated; the approaches of staff provide residents with different opportunities and limitations and also yield unintended consequences for the social life of residents. The two different general approaches are, we suggest, "cultural expressions," conditioned by more than official preferences and recommendations. The difference between the institutions is, in other words, anchored in ideas and ideologies that are not explicitly addressed.

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)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0540.001
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 head0.210
GPT teacher head0.541
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 teacher head, not a consensus.

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

Citations9
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueHealth An Interdisciplinary Journal for the Social Study of Health Illness and MedicineSame topicGeriatric Care and Nursing HomesFrench-language works237,207