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Record W2776566506 · doi:10.25133/jpssv26n1.001

Perceptions of Eldercare Service Needs: A Chinese-Canadian Community Survey

2017· article· en· W2776566506 on OpenAlexaffabout
Henry P. H. Chow

Bibliographic record

VenueJournal of Population and Social Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsPerceptionService (business)Survey researchPsychologyBusinessPublic relationsPolitical scienceMarketingApplied psychology

Abstract

fetched live from OpenAlex

Ethnic minority immigrants, especially those who resettle in a foreign country in the later stages of life, face many challenges as they age. A community survey using a representative sample of Chinese-Canadians aged 18 or above was undertaken to explore perceptions towards eldercare service needs among Chinese seniors. Telephone interviews were conducted with 336 Chinese-Canadians residing in a western Canadian city (Calgary, Alberta) by trained, bilingual interviewers using a structured questionnaire on topics such as perceived eldercare needs of Chinese seniors, household composition, and socio-demographic information. Multiple ordinary least-squares regression analysis demonstrated that age, country of origin, perceived service needs, health of seniors in household, length of residence in Canada, and sense of filial responsibility are significantly related to respondents’ support for ethnic eldercare services. The findings underscore the importance of culturally and linguistically sensitive eldercare services and programs in the Chinese community.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.084
GPT teacher head0.394
Teacher spread0.310 · 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 designObservational
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

Citations1
Published2017
Admission routes2
Has abstractyes

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