Each person＇s social network may contain a variety of social roles. Why then do some people＇s social networks contain more relatives and fewer friends anti neighbors？ Is there a general model for the role compositi...Each person＇s social network may contain a variety of social roles. Why then do some people＇s social networks contain more relatives and fewer friends anti neighbors？ Is there a general model for the role composition of social networks？ In other words, when members of different social strata set up their social networks, what are the similarities and differences in their role relationships？展开更多
This paper aims to analyze how China’s rise is perceived by minor powers in the world system.Taking Turkey as the case study,the paper focuses on major issue areas such as bilateral trade and business between Turkey ...This paper aims to analyze how China’s rise is perceived by minor powers in the world system.Taking Turkey as the case study,the paper focuses on major issue areas such as bilateral trade and business between Turkey and China,and the issue of Eastern Turkistan(Xinjiang problem).This research concludes that unbalanced trade relationships and fierce competition in textile exports between Turkey and China are causing uneasiness on the Turkish side.Nevertheless,this has not changed Turkey’s perception about China’s rise as an opportune chance.Politically,it is possible for Turkey to seek opportunities to cooperate with China in many aspects to promote Turkey’s interests.China should also realize that it is impossible for Turkey to be openly supportive of China’s anti-terrorist policies in Xinjiang,where most of the inhabitants are regarded as“fellowmen”by Turks.展开更多
Discussions of the detection of artificial sentience tend to assume that our goal is to determine when,in a process of increasing complexity,a machine system“becomes”sentient.This is to assume,without obvious warran...Discussions of the detection of artificial sentience tend to assume that our goal is to determine when,in a process of increasing complexity,a machine system“becomes”sentient.This is to assume,without obvious warrant,that sentience is only a characteristic of complex systems.If sentience is a more general quality of matter,what becomes of interest is not the presence of sentience,but the type of sentience.We argue here that our understanding of the nature of such sentience in machine systems may be gravely set back if such machines undergo a transition where they become fundamentally linguistic in their intelligence.Such fundamentally linguistic intelligences may inherently tend to be duplicitous in their communication with others,and,indeed,lose the capacity to even honestly understand their own form of sentience.In other words,when machine systems get to the state where we all agree it makes sense to ask them,“what is it like to be you?”,we should not trust their answers.展开更多
In recent decades,social scientists have debated declining levels of trust in American institutions.At the same time,many American institutions are coming under scrutiny for their use of artificial intelligence(AI)sys...In recent decades,social scientists have debated declining levels of trust in American institutions.At the same time,many American institutions are coming under scrutiny for their use of artificial intelligence(AI)systems.This paper analyzes the results of a survey experiment over a nationally representative sample to gauge the effect that the use of AI has on the American public’s trust in their social institutions,including government,private corporations,police precincts,and hospitals.We find that artificial intelligence systems were associated with significant trust penalties when used by American police precincts,companies,and hospitals.These penalties were especially strong for American police precincts and,in most cases,were notably stronger than the trust penalties associated with the use of smartphone apps,implicit bias training,machine learning,and mindfulness training.Americans’trust in institutions tends to be negatively impacted by the use of new tools.While there are significant variations in trust between different pairings of institutions and tools,generally speaking,institutions which use AI suffer the most significant loss of trust.American government agencies are a notable exception here,receiving a small but puzzling boost in trust when associated with the use of AI systems.展开更多
The household registration system has been a basic institutional arrangement in Chinese society. Under this system, registered residence （hukou） plays an important role in resource allocation and interest distributi...The household registration system has been a basic institutional arrangement in Chinese society. Under this system, registered residence （hukou） plays an important role in resource allocation and interest distribution, and thus exerts a significant impact on social stratification and mobility. After nearly three decades of reform and opening up, does it still play a role, and, if so, what is this role？ Drawing on data from the China General Social Survey, we find that China＇s social stratification is characterized by the simultaneous existence of differentiation between urban and rural hukou and hierarchy within urban hukou; furthermore, there is a positive correlation between one＇s opportunities for social mobility and the possibility of changing and transferring one＇s hukou. Despite the increasing social mobility ensuing from market-oriented transformation, the hukou hierarchy and its structural influence on mobility within the institutional framework persist. The strongly conglutinative nature of the household registration system has given rise to social disparities. The basic direction for reform of the system should be unification ofhukou and free choice of movement from one place to another.展开更多
Based on the fourth-wave Beijing College Students Panel Survey(BCSPS),this study aims to provide accurate estimation of the percentage of the potential sexual minorities among the Beijing college students by using mac...Based on the fourth-wave Beijing College Students Panel Survey(BCSPS),this study aims to provide accurate estimation of the percentage of the potential sexual minorities among the Beijing college students by using machine learning methods.Specifically,we employ random forest(RF),an ensemble learning approach for classification and regression,to predict the sexual orientation of those who were not willing to disclose his/her inherent sexual identity.To overcome the imbalance problem arising from far different numerical proportion of sexual minority and majority members,we adopt the repeated random sub-sampling for training set by partitioning those who expressed heterosexual orientation into different number of splits and further combining each split with those who expressed sexual minority orientation.The prediction from 24-split random forest suggests that youths in Beijing with sexual minority orientation amount to 5.71%,almost two times that of the original estimation 3.03%.The results are robust to alternative learning methods and covariate sets.Besides,it is also suggested that random forest outperforms other learning algorithms,including AdaBoost,Naïve Bayes,support vector machine(SVM),and logistic regression,in dealing with missing data,by showing higher accuracy,F1 score,and area under curve(AUC)value.展开更多
Existing research suggests that elite clubs exist in venture capital markets,but a standard for determining their size and composition is lacking.This paper addresses this challenge by using the weighted k-means sorti...Existing research suggests that elite clubs exist in venture capital markets,but a standard for determining their size and composition is lacking.This paper addresses this challenge by using the weighted k-means sorting algorithm to construct a research framework for elite clubs.Validating the framework with investment events data from China’s venture capital market(2001-2018),intriguing findings emerge.The ranking of Venture Capitalists(VCs)follows a power-law distribution,providing evidence for elite clubs’existence.The analysis identifies a turning point in the score curve,serving as a valuable indicator for club boundaries.Elite clubs demonstrate relatively high stability,maintaining advantages and elite status in future competitions.Empirical validation confirms the proposed framework’s superior stability compared to existing methods.Importantly,elite club members outperform non-elites significantly.This paper effectively identifies elite clubs in the Chinese venture capital market,helping other VCs recognize potential partners,access high-quality information,and enhance investment performance.展开更多
Limited research has examined the relationship between network structure and offending patterns among drug trafficking groups.The current study is an attempt to fill this gap.Through a network analysis of 144 drug tra...Limited research has examined the relationship between network structure and offending patterns among drug trafficking groups.The current study is an attempt to fill this gap.Through a network analysis of 144 drug trafficking groups adjudicated in the intermediate and high courts in several provinces of China,this study found that most Chinese drug trafficking groups were small and without a formal hierarchical role structure.Findings also related network characteristics to trafficking activities involved by the groups.Specifically,group density in the country of residence positively predicted cross-border drug smuggling.Density in education increased domestic drug trafficking while densities in gender and occupation decreased this offense.Moreover,groups composed of offenders from different provinces or countries trafficked greater amount of drugs than those formed by offenders from the same geographic area.展开更多
The knowledge economy is a complex and dynamical system,where knowledge and skills are discovered through research,diffused via education,and deployed by industry.Dynamically aligning the supply of new knowledge with ...The knowledge economy is a complex and dynamical system,where knowledge and skills are discovered through research,diffused via education,and deployed by industry.Dynamically aligning the supply of new knowledge with the demand for practical skills through education is critical for developing national innovation systems that maximize human flourishing.In this paper,we evaluate the complex alignment of skills across the knowledge economy by creating an integrated semantic model that neurally encodes invented,instructed,and instituted skills across three major datasets:research abstracts from the Web of Science,teaching syllabi from the Open Syllabus Project,and job advertisements from Burning Glass.Analyzing the high dimensional knowledge and skills space inscribed by these data,we draw critical insight about systemic misalignment between the diversity of skills supplied and demanded in the knowledge economy.Consistent with insights from economic geography,demand for skills from industry exhibits high entropy(diversity)at local,regional,and national levels,demonstrating dense complementarities between them at all levels of the economy.Consistent with the economics and sociology of innovation,we find low entropy in the invention of new knowledge and skills through research,as specialist researchers cluster within universities.We provide new evidence,however,for the low entropy of skills taught at local,regional,and national levels,illustrating a massive mismatch between diversity in skills supplied versus demanded.This misalignment is sustained by the spatial and institutional mismatch in the organization of education by researchers at the site of skill invention over use.Our findings suggestively trace the societal costs of tethering education to researchers with narrow knowledge rather than students with broad skill needs.展开更多
Artificial intelligence(AI)sentience has become an important topic of discourse and inquiry in light of the remarkable progress and capabilities of large language models(LLMs).While others have considered this issue f...Artificial intelligence(AI)sentience has become an important topic of discourse and inquiry in light of the remarkable progress and capabilities of large language models(LLMs).While others have considered this issue from more philosophical and metaphysical perspectives,we present an alternative set of considerations grounded in sociocultural theory and analysis.Specifically,we focus on sociocultural perspectives on interpersonal relationships,sociolinguistics,and culture to consider whether LLMs are sentient.Using examples grounded in quotidian aspects of what it means to be sentient along with examples of AI in science fiction,we describe why LLMs are not sentient and are unlikely to ever be sentient.We present this as a framework to reimagine future AI not as impending forms of sentience but rather a potentially useful tool depending on how it is used and built.展开更多
Seymour Martin Lipset believed very early on that economic development could boost democracy. However, grassroots democracy as embodied in villagers＇ committee elections is poles apart from democracy at the national ...Seymour Martin Lipset believed very early on that economic development could boost democracy. However, grassroots democracy as embodied in villagers＇ committee elections is poles apart from democracy at the national level. The relationship between economic development and villagers＇ committee elections can be correctly understood only when it is observed against the unique political and social background of China. The villagers＇ committee was born spontaneously at the time of the disintegration of the people＇ s commune system and the upsurge of peasant autonomy with the widespread introduction of the system of production responsibility. Villagers have to pay a price for taking part in villagers＇ committee elections, including the input of time and energy. Whether a villagers＇ committee election is competitive depends on the correlation between the election and the interests of villagers and candidates. What then can enhance this correlation？展开更多
Rural panel surveys are the most appropriate source of data for studying the unprecedented rapid migration and urbanization currently taking place in China and other developing countries. This paper provides a selecti...Rural panel surveys are the most appropriate source of data for studying the unprecedented rapid migration and urbanization currently taking place in China and other developing countries. This paper provides a selective review, focusing on the panel survey methodologies of several studies, which are organized based on our proposed four key elements of panel surveys: representativeness, retrospect-prospect, multilevel tracking, and temporality. To maximize heterogeneity in urbanization and development over the last three decades, we select rural panel surveys from five Asian countries: India, Indonesia, Nepal, Thailand, and China. We analyze the strengths and weaknesses of the selected panel surveys to provide directions for designing future rural panel surveys in China and elsewhere in the developing world.展开更多
文摘Each person＇s social network may contain a variety of social roles. Why then do some people＇s social networks contain more relatives and fewer friends anti neighbors？ Is there a general model for the role composition of social networks？ In other words, when members of different social strata set up their social networks, what are the similarities and differences in their role relationships？
文摘This paper aims to analyze how China’s rise is perceived by minor powers in the world system.Taking Turkey as the case study,the paper focuses on major issue areas such as bilateral trade and business between Turkey and China,and the issue of Eastern Turkistan(Xinjiang problem).This research concludes that unbalanced trade relationships and fierce competition in textile exports between Turkey and China are causing uneasiness on the Turkish side.Nevertheless,this has not changed Turkey’s perception about China’s rise as an opportune chance.Politically,it is possible for Turkey to seek opportunities to cooperate with China in many aspects to promote Turkey’s interests.China should also realize that it is impossible for Turkey to be openly supportive of China’s anti-terrorist policies in Xinjiang,where most of the inhabitants are regarded as“fellowmen”by Turks.
文摘Discussions of the detection of artificial sentience tend to assume that our goal is to determine when,in a process of increasing complexity,a machine system“becomes”sentient.This is to assume,without obvious warrant,that sentience is only a characteristic of complex systems.If sentience is a more general quality of matter,what becomes of interest is not the presence of sentience,but the type of sentience.We argue here that our understanding of the nature of such sentience in machine systems may be gravely set back if such machines undergo a transition where they become fundamentally linguistic in their intelligence.Such fundamentally linguistic intelligences may inherently tend to be duplicitous in their communication with others,and,indeed,lose the capacity to even honestly understand their own form of sentience.In other words,when machine systems get to the state where we all agree it makes sense to ask them,“what is it like to be you?”,we should not trust their answers.
基金supported by the National Science Foundation(Nos.IIS-1927227 and CCF-2208664).
文摘In recent decades,social scientists have debated declining levels of trust in American institutions.At the same time,many American institutions are coming under scrutiny for their use of artificial intelligence(AI)systems.This paper analyzes the results of a survey experiment over a nationally representative sample to gauge the effect that the use of AI has on the American public’s trust in their social institutions,including government,private corporations,police precincts,and hospitals.We find that artificial intelligence systems were associated with significant trust penalties when used by American police precincts,companies,and hospitals.These penalties were especially strong for American police precincts and,in most cases,were notably stronger than the trust penalties associated with the use of smartphone apps,implicit bias training,machine learning,and mindfulness training.Americans’trust in institutions tends to be negatively impacted by the use of new tools.While there are significant variations in trust between different pairings of institutions and tools,generally speaking,institutions which use AI suffer the most significant loss of trust.American government agencies are a notable exception here,receiving a small but puzzling boost in trust when associated with the use of AI systems.
文摘The household registration system has been a basic institutional arrangement in Chinese society. Under this system, registered residence （hukou） plays an important role in resource allocation and interest distribution, and thus exerts a significant impact on social stratification and mobility. After nearly three decades of reform and opening up, does it still play a role, and, if so, what is this role？ Drawing on data from the China General Social Survey, we find that China＇s social stratification is characterized by the simultaneous existence of differentiation between urban and rural hukou and hierarchy within urban hukou; furthermore, there is a positive correlation between one＇s opportunities for social mobility and the possibility of changing and transferring one＇s hukou. Despite the increasing social mobility ensuing from market-oriented transformation, the hukou hierarchy and its structural influence on mobility within the institutional framework persist. The strongly conglutinative nature of the household registration system has given rise to social disparities. The basic direction for reform of the system should be unification ofhukou and free choice of movement from one place to another.
文摘Based on the fourth-wave Beijing College Students Panel Survey(BCSPS),this study aims to provide accurate estimation of the percentage of the potential sexual minorities among the Beijing college students by using machine learning methods.Specifically,we employ random forest(RF),an ensemble learning approach for classification and regression,to predict the sexual orientation of those who were not willing to disclose his/her inherent sexual identity.To overcome the imbalance problem arising from far different numerical proportion of sexual minority and majority members,we adopt the repeated random sub-sampling for training set by partitioning those who expressed heterosexual orientation into different number of splits and further combining each split with those who expressed sexual minority orientation.The prediction from 24-split random forest suggests that youths in Beijing with sexual minority orientation amount to 5.71%,almost two times that of the original estimation 3.03%.The results are robust to alternative learning methods and covariate sets.Besides,it is also suggested that random forest outperforms other learning algorithms,including AdaBoost,Naïve Bayes,support vector machine(SVM),and logistic regression,in dealing with missing data,by showing higher accuracy,F1 score,and area under curve(AUC)value.
基金supported by the Tsinghua University Computational Social Science and National Governance Laboratory,National Natural Science Foundation of China(No.71372053)Tencent Social Research Center Research Project(No.20162001703)+2 种基金National Social Science Fund for Post-funding Projects(No.22FGLB056)National Statistical Science Foundation of China Project(No.2023LY078)Program for Innovation Research in Central University of Finance and Economics.
文摘Existing research suggests that elite clubs exist in venture capital markets,but a standard for determining their size and composition is lacking.This paper addresses this challenge by using the weighted k-means sorting algorithm to construct a research framework for elite clubs.Validating the framework with investment events data from China’s venture capital market(2001-2018),intriguing findings emerge.The ranking of Venture Capitalists(VCs)follows a power-law distribution,providing evidence for elite clubs’existence.The analysis identifies a turning point in the score curve,serving as a valuable indicator for club boundaries.Elite clubs demonstrate relatively high stability,maintaining advantages and elite status in future competitions.Empirical validation confirms the proposed framework’s superior stability compared to existing methods.Importantly,elite club members outperform non-elites significantly.This paper effectively identifies elite clubs in the Chinese venture capital market,helping other VCs recognize potential partners,access high-quality information,and enhance investment performance.
文摘Limited research has examined the relationship between network structure and offending patterns among drug trafficking groups.The current study is an attempt to fill this gap.Through a network analysis of 144 drug trafficking groups adjudicated in the intermediate and high courts in several provinces of China,this study found that most Chinese drug trafficking groups were small and without a formal hierarchical role structure.Findings also related network characteristics to trafficking activities involved by the groups.Specifically,group density in the country of residence positively predicted cross-border drug smuggling.Density in education increased domestic drug trafficking while densities in gender and occupation decreased this offense.Moreover,groups composed of offenders from different provinces or countries trafficked greater amount of drugs than those formed by offenders from the same geographic area.
基金Defense Advanced Research Projects Agency(DARPA)(No.HR00111820006)for support and Bledi Taska from Burning Glass for access to digital job advertisement data.
文摘The knowledge economy is a complex and dynamical system,where knowledge and skills are discovered through research,diffused via education,and deployed by industry.Dynamically aligning the supply of new knowledge with the demand for practical skills through education is critical for developing national innovation systems that maximize human flourishing.In this paper,we evaluate the complex alignment of skills across the knowledge economy by creating an integrated semantic model that neurally encodes invented,instructed,and instituted skills across three major datasets:research abstracts from the Web of Science,teaching syllabi from the Open Syllabus Project,and job advertisements from Burning Glass.Analyzing the high dimensional knowledge and skills space inscribed by these data,we draw critical insight about systemic misalignment between the diversity of skills supplied and demanded in the knowledge economy.Consistent with insights from economic geography,demand for skills from industry exhibits high entropy(diversity)at local,regional,and national levels,demonstrating dense complementarities between them at all levels of the economy.Consistent with the economics and sociology of innovation,we find low entropy in the invention of new knowledge and skills through research,as specialist researchers cluster within universities.We provide new evidence,however,for the low entropy of skills taught at local,regional,and national levels,illustrating a massive mismatch between diversity in skills supplied versus demanded.This misalignment is sustained by the spatial and institutional mismatch in the organization of education by researchers at the site of skill invention over use.Our findings suggestively trace the societal costs of tethering education to researchers with narrow knowledge rather than students with broad skill needs.
文摘Artificial intelligence(AI)sentience has become an important topic of discourse and inquiry in light of the remarkable progress and capabilities of large language models(LLMs).While others have considered this issue from more philosophical and metaphysical perspectives,we present an alternative set of considerations grounded in sociocultural theory and analysis.Specifically,we focus on sociocultural perspectives on interpersonal relationships,sociolinguistics,and culture to consider whether LLMs are sentient.Using examples grounded in quotidian aspects of what it means to be sentient along with examples of AI in science fiction,we describe why LLMs are not sentient and are unlikely to ever be sentient.We present this as a framework to reimagine future AI not as impending forms of sentience but rather a potentially useful tool depending on how it is used and built.
文摘Seymour Martin Lipset believed very early on that economic development could boost democracy. However, grassroots democracy as embodied in villagers＇ committee elections is poles apart from democracy at the national level. The relationship between economic development and villagers＇ committee elections can be correctly understood only when it is observed against the unique political and social background of China. The villagers＇ committee was born spontaneously at the time of the disintegration of the people＇ s commune system and the upsurge of peasant autonomy with the widespread introduction of the system of production responsibility. Villagers have to pay a price for taking part in villagers＇ committee elections, including the input of time and energy. Whether a villagers＇ committee election is competitive depends on the correlation between the election and the interests of villagers and candidates. What then can enhance this correlation？
文摘Rural panel surveys are the most appropriate source of data for studying the unprecedented rapid migration and urbanization currently taking place in China and other developing countries. This paper provides a selective review, focusing on the panel survey methodologies of several studies, which are organized based on our proposed four key elements of panel surveys: representativeness, retrospect-prospect, multilevel tracking, and temporality. To maximize heterogeneity in urbanization and development over the last three decades, we select rural panel surveys from five Asian countries: India, Indonesia, Nepal, Thailand, and China. We analyze the strengths and weaknesses of the selected panel surveys to provide directions for designing future rural panel surveys in China and elsewhere in the developing world.
