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Record W1499658182

Aging wellbeing and social security in rural northern China.

2000· article· en· W1499658182 on OpenAlexaff
Dwayne Benjamin, Loren Brandt, Scott Rozelle

Bibliographic record

VenuePopulation and Development Review · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSocial securityChinaRural areaEconomic growthPosition (finance)Elderly peopleInstitutionEconomic securityConsumption (sociology)SocioeconomicsDevelopment economicsDemographic economicsPolitical scienceSociologyEconomicsGerontologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

This paper aims to provide an overview of the factual background to several issues concerning aging well-being and social security in rural northern China. These are: living conditions of Chinese rural elderly the economic circumstances of the elderly whether retirement is a meaningful concept in rural China and the relative economic standing of the elderly as indicated by their income and consumption levels. Data from three surveys are utilized: the first was conducted in 1995; the second used historical comparison which covers 1935; and the third contains 1989 data. Overall findings regarding the living conditions of the Chinese rural elderly indicate that an urban bias reflected in other aspects of public policy extends to the provision of social security. No foundation for the notion that the rural elderly are well cared for - at least in comparison with the urban elderly is noted. Moreover most evidence points to a relative deterioration of the economic position of the elderly in rural areas and a weakening of the family as a social security institution.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.285
Teacher spread0.275 · 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

Citations60
Published2000
Admission routes1
Has abstractyes

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