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Record W2767088388 · doi:10.1177/1049732317737979

“Leisurely Dining”: Exploring How Work Organization, Informal Care, and Dining Spaces Shape Residents’ Experiences of Eating in Long-Term Residential Care

2017· article· en· W2767088388 on OpenAlexaffabout
Ruth Lowndes, Tamara Daly, Pat Armstrong

Bibliographic record

VenueQualitative Health Research · 2017
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsYork University
Fundersnot available
KeywordsStaffingAusterityEthnographyWork (physics)NursingLong-term careParticipant observationData collectionPsychologyAged carePoliticsSociologyMedicinePolitical science

Abstract

fetched live from OpenAlex

Mealtimes are among the busiest times in nursing homes. Austerity measures resulting in insufficient staff with heavy workloads limit the amount of time available to assist residents with eating. Within a feminist political economy framework, rapid team-based ethnography was used for an international study involving six countries exploring promising practices and also for a study conducted in one Canadian province in which interrelationships between formal and informal care were investigated. Data collection methods included interviews and observations. In addition, dining maps were completed providing a cross-jurisdictional comparison of mealtime work organization, and illustrating the time spent assisting residents with meals. Dining maps highlight the reliance on unpaid care as well as how low staffing levels leave care providers rushing around, preventing a pleasurable resident dining experience, which is central to 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 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)0.005
metaresearch head score (Gemma)0.007
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 score0.031
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.407
GPT teacher head0.577
Teacher spread0.170 · 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

Citations33
Published2017
Admission routes2
Has abstractyes

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