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Record W2946604632 · doi:10.1111/ajag.12671

Caregiving, ethnicity and gender in Māori and non‐Māori New Zealanders of advanced age: Findings from Li<scp>LACS NZ</scp> Kaiāwhina (Love and Support) study

2019· article· en· W2946604632 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAustralasian Journal on Ageing · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsnot available
FundersHealth Research Council of New ZealandMinistry of Health, British Columbia
KeywordsEthnic groupLongitudinal studyPsychologyGerontologyMedicineSociology

Abstract

fetched live from OpenAlex

OBJECTIVE: This study investigates sex and ethnicity in relationships of care using data from Wave 4 of LiLACS NZ, a longitudinal study of Māori and non-Māori New Zealanders of advanced age. METHODS: Informal primary carers for LiLACS NZ participants were interviewed about aspects of caregiving. Data were analysed by gender and ethnic group of the LiLACS NZ participant. RESULTS: Carers were mostly adult children or partners, and three-quarters of them were women. Māori and men received more hours of care with a higher estimated dollar value of care. Māori men received the most personal care and household assistance. Carer employment, self-rated health, quality of life and impact of caring did not significantly relate to the gender and ethnicity of care recipients. CONCLUSIONS: Gender and ethnicity are interwoven in caregiving and care receiving. Demographic differences and cultural expectations in both areas must be considered in policies for carer support.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.141
Threshold uncertainty score0.815

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.017
GPT teacher head0.291
Teacher spread0.274 · 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