MétaCan
Menu
Back to cohort

Rural Social Security System of China: Problems and Solutions

2014· article· en· W1941272581 on OpenAlexvenueno aff
Juan Chen, Shaolei Yang

Bibliographic record

VenueStudies in sociology of science · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsSocial securityChinaBusinessModernization theoryRural areaEconomic growthSecurity studiesNetwork security policySecurity managementSecurity convergenceEconomic securityCritical security studiesSecurity servicePolitical scienceEconomicsComputer securityPublic administrationInformation securityFinanceMarket economyComputer science

Abstract

fetched live from OpenAlex

An all-round rural social security system of China has a very important strategic effect on the Chinese development of agriculture and country, along with Chinese modernization construction. After decades of efforts, construction of the rural social security system of China has got the obvious achievements. However, many problems of the rural social security system still exist, which evidently reflect those fields such as the narrow coverage of social security, the low social security level and the limited financing channels of social security funds. In the following development, many measures should be taken to perfect the rural social security system of China, including clarifying the construction emphasis of the rural social security system, increasing the governmental investment in the rural social security system, setting up the unified management system of social security, doing well the propaganda and service work of the rural social security, as well as perfecting the supervision system of the rural social security.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.168

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0040.003
Scholarly communication0.0040.004
Open science0.0020.004
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.077
GPT teacher head0.409
Teacher spread0.333 · 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

Citations8
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueStudies in sociology of scienceSame topicEducation Systems and PolicyFrench-language works237,207