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Record W2375902835

Characteristic analysis of farmer household'social capital in Zhangye City

2013· article· en· W2375902835 on OpenAlexaff
Zhao Xue-ya

Bibliographic record

VenueGanhanqu dili · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Capital and Networks
Canadian institutionsScience North
Fundersnot available
KeywordsSocial capitalIndex (typography)Household incomeSocial mobilitySocioeconomicsFinancial capitalDemographic economicsEconomic growthBusinessGeographyEconomicsHuman capitalSociologySocial science
DOInot available

Abstract

fetched live from OpenAlex

The study of the social capital and its relationships with the development is a topical subject.As one of the important factors affecting the sustainable development,social capital plays a very important role in the social and economic development in a country or region.This paper takes Zhangye City,Gansu Province,China as the research area,in which it is famous forThe Silk Road,and designs the measurement index of social capital.It uses the farmer households survey datas and principal component analysis method to calculate social capital index and then analyzes the social capital factors.Finally,the paper also analyzes the factors that are influencing the social capital.The results show as follows:(1)Social capital index in Zhangye City is 4.93.The trust and solidarity dimension maintain the highest development level,while the information dissemination dimension maintains the minimum development level.(2)There are hosts of differences in the influencing factors of different dimensions of the social capital.The factors influencing the trust dimension basically are the householders' educational level and the wealth differences.The factors influencing the political empowerment dimensions are the householders' educational level and the age of the head of the household.The factors influencing the network dimension are the householders' educational level、the average annual income and the age of the head of the household.The influencing factors of the cooperation dimensions are the householders' educational level、the average annual income and the age of the head of the household and the wealth differences.The influencing factors of the social cohesion dimension are the householders' educational level、the age of the head of the household and the wealth differences.However,the influencing factors of the information dissemination dimension are the householders' educational level、the average annual income and the wealth differences among the householders.(3)The stock of social capital can be improved increasingly.It is significant to strengthen the investment and construction of the trust dimension、develop the folk organizations to improve the ability of obtaining the information by the telephone、the internet、the TV and so on and continue to make the officials and the villagers committee serve the people heart and soul.Meanwhile,local government should increase the opportunity of employment with local conditions、strengthen infrastructure construction to improve the telephone and the internet coverage and held science and technology culture month activities to improve their education level.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.033
GPT teacher head0.285
Teacher spread0.252 · 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 designQualitative
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

Citations1
Published2013
Admission routes1
Has abstractyes

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