Linguistic occupation segregation along the U.S.–Mexico border: using the index of dissimilarity to measure inequality in employment among monolingual speakers and Spanish–English bilinguals

The U.S.–Mexico border is a Latina/o concentrated region and Spanish–English bilingual society. While there are some indications of an economic advantage associated with Spanish–English bilingualism in regions with over-representations of Spanish-origin speakers, the degree of occupational linguistic segregation in such ethno-linguistic context is unknown. Based on data from the American Community Survey (ACS) Public Use Microdata Sample (PUMS) for 2018, this study calculates the occupational dissimilarity index (D) among monolingual-Spanish speakers, Spanish–English bilinguals, and monolingual-English speakers for cities located along the Texas–Mexico border and in the Houston metropolis. Findings show that the highest occupational segregation is found between monolingual-Spanish speakers and both monolingual-English and Spanish–English bilinguals. This indicates that the monolingual-Spanish workforce is occupationally segregated from those with fluent command of English. The lowest occupation dissimilarity indices are between Spanish–English bilinguals and monolingual-English speakers, indicating that these groups are approaching similar occupational placements. I conclude by highlighting an occupational advantage to Spanish–English bilingualism, but only in border cities characterised by concentrations of Spanish-origin speakers. In the non-border city of Houston, being Spanish–English bilingual is not enough to experience occupational upward mobility.

Fine-scale Population Structure and Demographic History of Han Chinese Inferred from Haplotype Network of 111,000 Genomes

ABSTRACTHan Chinese is the most populated ethnic group across the globe with a comprehensive substructure that resembles its cultural diversification. Studies have constructed the genetic polymorphism spectrum of Han Chinese, whereas high-resolution investigations are still missing to unveil its fine-scale substructure and trace the genetic imprints for its demographic history. Here we construct a haplotype network consisted of 111,000 genome-wide genotyped Han Chinese individuals from direct-to-consumer genetic testing and over 1.3 billion identity-by-descent (IBD) links. We observed a clear separation of the northern and southern Han Chinese and captured 5 subclusters and 17 sub-subclusters in haplotype network hierarchical clustering, corresponding to geography (especially mountain ranges), immigration waves, and clans with cultural-linguistic segregation. We inferred differentiated split histories and founder effects for population clans Cantonese, Hakka, and Minnan-Chaoshanese in southern China, and also unveiled more recent demographic events within the past few centuries, such as Zou Xikou and Chuang Guandong. The composition shifts of the native and current residents of four major metropolitans (Beijing, Shanghai, Guangzhou, and Shenzhen) imply a rapidly vanished genetic barrier between subpopulations. Our study yields a fine-scale population structure of Han Chinese and provides profound insights into the nation’s genetic and cultural-linguistic multiformity.

Dimensions of Ethnic Diversity and Underground Economic Activity: Cross-country Evidence

Cultural and ethnic factors crucially affect economic agents’ propensities toward law-abiding behavior and operating in the underground economy is an important, widely prevalent, aspect. However, there are many dimensions of ethnic diversity, and the relative influences of each on underground behavior are not well articulated. This article uniquely considers the effects of five dimensions of ethnic/cultural diversity, including ethnic income inequality, ethnic–linguistic fragmentation, cultural fragmentation, ethnolinguistic polarization, and ethnic–linguistic segregation, on the international shadow economy. Placing the empirical analysis in the context of the empirical determinants of the shadow economy, results show income inequality across ethnic groups increases underground activity across different modeling variations, while the effects of the other dimensions are statistically insignificant. This unique finding underscores the notion that not all dimensions of ethnic diversity are alike when it comes to their influences on the informal sector.