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Record W6926706358 · doi:10.25384/sage.c.4119791.v1

‘It’s Like Chicken Talking to Ducks’ and Other Challenges to Families of Chinese Immigrant Older Adults in Long-Term Residential Care

2018· other· en· W6926706358 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2018
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicBotanical Research and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationResidential carePerceptionQuality of life (healthcare)Sample (material)Quality (philosophy)Nursing homes

Abstract

fetched live from OpenAlex

Immigrant older adults are increasingly moving into long term residential care (LTRC) homes; however, most were designed and continue to be run in accordance with Anglocentric norms and values. Participation and interest in Family Councils—through which they might collectively voice concerns—was low within our purposive sample of nine Chinese-origin residents living in LTRC homes and 11 family carers. Our study, conducted in two LTRC homes in British Columbia, Canada between January and March 2016, further explored participants’ perceptions of quality of care by staff and quality of life of residents. Our findings negate participants’ rationale that they do not attend because they have no issues to raise. Solutions must recognize that carers’ time is precious and care-work is gendered; language incongruity and failure to address it marginalizes residents and their family members. A culturally informed reticence to speak out is reinforced when attempts to do so are silenced.

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)0.006
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: Other · Consensus signal: none
Teacher disagreement score0.088
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0090.005
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.037
GPT teacher head0.327
Teacher spread0.290 · 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
GenreOther

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

Citations0
Published2018
Admission routes1
Has abstractyes

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