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Living Standard, Living Level and Economic Wellbeing of Older Persons: Similarity and Differences in Measuring These Concepts

2010· article· en· W1899451633 on OpenAlexvenueno aff
Benjamin Chan Yin-Fah

Bibliographic record

VenueCanadian social science · 2010
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsnot available
Fundersnot available
KeywordsWelfare economicsStandard of livingPopulation ageingPopulationHumanitiesSociologyPolitical scienceEconomicsPsychologyDemographyArt

Abstract

fetched live from OpenAlex

The number of older persons is increasing throughout the world and the consequences of ageing population; specifically in economics of aging was deserved to be being attention. The main issue in economics of aging is the way in indentifying the economically vulnerable group and how the allocate government’s limited resources to the needed group. However, various methods, either using objective approach (income, consumption, net flow, net worth) or subjective approach (self-rated income adequacy, perceived financial satisfaction) were employed to identify the vulnerable group. This paper aims to link concept of economic status, economic well being with living level and living standard. It recommended that those who want to study the concept of economic well being should start from the understanding of living level and living standard. Key words: Older person; living level and living standardResume: Le nombre de personnes âgees est en augmentation partout dans le monde et les consequences du vieillissement de la population, en particulier dans l'economie du vieillissement, meritaient d'etre suivies de pres. La question principale dans l'economie du vieillissement est la facon d'identifier le groupe economiquement vulnerable et comment allouer les ressources limitees du gouvernement au groupe de besoin. Or, des methodes diverses, soit en utilisant l'approche objective (le revenu, la consommation, le flux net, la valeur nette) ou l'approche subjective (l'adequation du revenu auto-evalue, la satisfaction financiere percue) ont ete utilisees pour identifier les groupes vulnerables. Ce document vise a relier la notion de statut economique, du bien-etre economique avec le niveau de vie et le standard vie. Il a recommande que ceux qui voulaient etudier la notion de bien-etre economique devraient commencer par la comprehension du niveau de vie et du standard de vie.Mots-cles: personnes âgees, standard de vie et niveau de vie

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)0.001
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 score0.077
Threshold uncertainty score0.961

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.043
GPT teacher head0.313
Teacher spread0.270 · 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.

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

Citations14
Published2010
Admission routes1
Has abstractyes

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