MétaCan
Menu
Back to cohort
Record W4200091386 · doi:10.1111/ajag.13031

Experiences and perceptions of ageing among older First Nations Australians: A rapid review

2021· review· en· W4200091386 on OpenAlexaboutno aff
Aryati Yashadhana, Adam Howie, Madelene Veber, Patricia Cullen, Adrienne Withall, Ebony Lewis, Ruth McCausland, Rona Macniven, Melanie Andersen

Bibliographic record

VenueAustralasian Journal on Ageing · 2021
Typereview
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
FundersUniversity of New South Wales
KeywordsMainstreamAgeingGerontologyOlder peoplePerceptionAged careHealthy ageingQualitative researchInclusion (mineral)Psychological resilienceAgeing societyMedicinePsychologySociologyPolitical scienceGender studiesSocial psychologySocial science

Abstract

fetched live from OpenAlex

OBJECTIVE: To identify and describe articles reporting the experiences and perceptions of ageing among older First Nations Australians. METHODS: Following rapid review and PRISMA guidelines, we searched five databases for peer-reviewed articles published prior to October 2019 that reported qualitative accounts of ageing among older (≥ 45 years) First Nations Australians. Data were extracted and synthesised thematically. RESULTS: Twenty-one articles were included in the final synthesis. Priorities in ageing highlighted the role of Elders, family, community, culture and connection to ancestral lands. Experiences and perceptions of ageing reflected cultural marginalisation in aged and health care services, and highlighted the importance of cultural identity, resilience and survival as key to ageing well. CONCLUSIONS: Our review suggests that mainstream ageing frameworks do not fully reflect the priorities of older First Nations Australians. This has important implications for ageing policy and the design and delivery of culturally safe aged and health care services.

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)0.014
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.036
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0130.011
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.044
GPT teacher head0.372
Teacher spread0.327 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations20
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAustralasian Journal on AgeingSame topicIndigenous Health, Education, and RightsFrench-language works237,207