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Reforma de las pensiones en China

2008· article· es· W2109587676 on OpenAlexaff
Felix Salditt, Peter Whiteford, Willem Adema

Bibliographic record

VenueRevista Internacional de Seguridad Social · 2008
Typearticle
Languagees
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsHumanitiesPolitical scienceGeographyArt

Abstract

fetched live from OpenAlex

Resumen Este artículo analiza el progreso conseguido en China en términos de creación de un sistema nacional de seguro de vejez, con una descripción detallada del sistema y una evaluación del grado en que ha conseguido, hasta el momento, realizar su principal objetivo de ofrecer seguridad social a más personas. Desde 1997 se han llevado a cabo muchas reformas pero, a pesar de los avances, el alcance del sistema es limitado, con una tasa de cobertura de los trabajadores urbanos inferior al 50 por ciento. La población rural sigue, en gran medida, sin tener cobertura del sistema, y es bastante posible que durante varios años aún la mayoría de la población siga dependiendo del apoyo familiar. Existe una «ventana demográfica» hasta 2015, aproximadamente, para hacer frente a estas deficiencias. Con el fin de crear un fundamento financiero e institucional que amortigüe los efectos en un futuro próximo de una población de edad mucho más avanzada será fundamental extender la cobertura mediante un mayor control del cumplimiento de sus obligaciones por parte de los trabajadores y las empresas y un compromiso financiero continuo orientado al Fondo Nacional de Seguridad Social.

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)0.002
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 score0.174
Threshold uncertainty score0.345

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.292
Teacher spread0.280 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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