This article seeks to compare genetic and patronymic diversity in mainland France. To do so, we discuss the small number of population genetics surveys that were carried out from the 20th century to ...the present day with the aim of describing the genetic diversity of mainland France as a whole. We highlight their present-day limitations, which result from their insufficient geographical coverage, the limited number of genetic systems included and/or the use of unsatisfactory methods of representation. To overcome these various drawbacks, our proposal is to use surnames as a substitute for genes, the advantages of this approach being their pattern of transmission, their huge number and their known frequency, down to the smallest administrative level across the whole of French territory and over several generations. The statistical results show the existence of strong patronymic disparities between the north and the south of France, and between the central and peripheral areas. The different patterns highlighted are closely linked to geographical proximity, but also to genetic, linguistic or dialectal variations, as well as to historical relationships with neighbouring countries.
In this paper, the Croatian and Ukrainian anthroponymic corpus are compared based on the twenty most common male and female names and surnames. The linguistic and cultural similarities between the ...Croatian and Ukrainian first name corpus are evidenced in the two most common Croatian and Ukrainian female names are Marija and Ana (Ukrainian Gana). Besides many homonymic or similar sounding modern Croatian and Ukrainian first names, the Croatian and Ukrainian first name corpora also include cognate local and historical forms for the Christian names Josip (Ukr. Osip) and Nikola (Cro. dial. Mikula and Ukr. Mikola). Smaller differences arise from the fact that Croatians are, for the most part, Catholic, while Ukrainians are, for the most part, Orthodox Christian, resulting in a portion of the Christian names used by Ukrainians having been directly borrowed from Greek (e.g., Grigorij), while they entered Croatian through Latin as an intermediary (e.g., Grgur). The most significant differences between the Croatians and Ukrainians lie in the surname corpus in which Croatian surnames originating from first names dominate, while in Ukraine surnames derived from terms for occupations dominate.
U ovome se radu na temelju dvadeset najčešćih muških i ženskih imena te prezimena uspoređuju hrvatski i ukrajinski antroponimijski fond. Jezične se i kulturološke sličnosti između hrvatskoga i ukrajinskoga osobnoimenskog fonda ogledaju u činjenici da su dva najčešća hrvatska i ukrajinska ženska imena Marija i (ukrajinski Gana). Osim velikoga broja istozvučnih ili bliskozvučnih suvremenih hrvatskih i ukrajinskih osobnih imena hrvatski i ukrajinski osobnoimenski fond ujedno bilježe i srodne mjesne i povijesne likove kršćanskih imena Josip (ukr. Osip) i Nikola (hrv. dij. Mikula i ukr. Mikola). Manje razlike proizlaze iz činjenice da su Hrvati uglavnom katolici, a Ukrajinci pravoslavci, pa su dio kršćanskih imena Ukrajinci primili izravno iz grčkoga jezika (npr. Grigorij), a Hrvati posredništvom latinskoga (npr. Grgur). Najveće su međusobne razlike između Hrvata i Ukrajinaca u prezimenskome fondu u kojemu u Hrvata prevladavaju prezimena potekla od osobnih imena, a u Ukrajinaca prezimena potekla od naziva zanimanja.česte u odlukama o početku ili prestanku pojedine mjere. Uljudniji oblici iskazivanja zapovijedi najrjeđi su među navedenim načinima, što sugerira važnost razumijevanja poruke o zaštiti sebe i drugih i, još više, djelovanja u skladu s njom.
Significant changes occurred in the late Chosŏn (Joseon) dynasty in terms of the formation of the Korean surname system we know today. The most noteworthy change of the surname system during this ...time was a drastic increase in the number of people who had newly acquired surnames. It is generally known that there was quite a large population of the “surname-less class (無姓層)” until the late Chosŏn dynasty. Who were these people who made up the surname-less class? What kind of social background allowed the people of the surname-less class to acquire surnames? The answers to these questions are related to the question of how all Koreans came to have their surnames today. This study attempts to explore this phenomenon of surname acquisition by the surname-less class and the social background which allowed this phenomenon to take place. The members of the surname-less class numbered about half of the population of Chosŏn only about 300 years ago in the late seventeenth century. During the eighteenth century, people who belonged to the surname-less class quickly began to acquire surnames, and as a result, most of the population of Chŏson had surnames by the first half of the nineteenth century. The rapid decline in the surname-less class population was directly related to the government’s policy on slaves (nobi). It can be understood as a result of the government’s policy to secure sufficient manpower for public service and the slaves’ intention to erase any trace of their former status after becoming yangin.
•CEO–board surname ties increase agency costs.•Monitoring by shareholders and supervisors reduces the effect of surname ties.•Aligning directors’ interests with firm value reduces the effect of ...surname ties.
Although corporate governance literature recognizes the influence of acquired social ties between CEOs and directors, innate social ties are hardly explored. To extend this literature, this study examines how CEO–board surname ties influence agency costs. Drawing on social identity theory, we first develop the argument that CEO–board surname ties result in increased agency costs. We then employ agency theory to examine the boundary conditions under which such directors are less likely to act as group members of surname ties. Specifically, we consider three key governance tools as such conditions, namely, monitoring by shareholders, aligning directors’ interests with firm value, and aligning supervisors’ interests with firm value. We find empirical support for our arguments by using a sample of 16,926 listed firms and 165,287 directors in China from 2005 to 2015. We discuss the contributions to corporate governance literature and elucidate the practical implications of our findings.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In the cultural context of “the children follow the father's surname,” the incorporation of both parents' surnames into the children's surnames (i.e., the “new compound surnames” phenomenon) reflects ...the conceptual change that occurred during the modernization of society. Using a sample of Chinese A-share listed firms from 2011 to 2020, this study examines whether firms led by CEOs with new compound surnames are associated with better environmental, social, and governance (ESG) performance. We find that firms led by CEOs with new compound surnames have significantly higher ESG performance scores. This finding holds after an array of robustness checks. We also find that the effect of CEOs with new compound surnames on ESG performance is more pronounced for non-state-owned enterprises, firms led by CEOs with lower personal economic motivation, and firms located in areas with higher marketization. Our study contributes to the research on executive characteristics and informal institutions by exploring the informativeness of CEOs' new compound surnames and has important implications for corporate governance.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The increasing impact of algorithmic decisions on people’s lives compels us to scrutinize their fairness and, in particular, the disparate impacts that ostensibly color-blind algorithms can have on ...different groups. Examples include credit decisioning, hiring, advertising, criminal justice, personalized medicine, and targeted policy making, where in some cases legislative or regulatory frameworks for fairness exist and define specific protected classes. In this paper we study a fundamental challenge to assessing disparate impacts in practice: protected class membership is often not observed in the data. This is particularly a problem in lending and healthcare. We consider the use of an auxiliary data set, such as the U.S. census, to construct models that predict the protected class from proxy variables, such as surname and geolocation. We show that even with such data, a variety of common disparity measures are generally unidentifiable, providing a new perspective on the documented biases of popular proxy-based methods. We provide exact characterizations of the tightest possible set of all possible true disparities that are consistent with the data (and possibly additional assumptions). We further provide optimization-based algorithms for computing and visualizing these sets and statistical tools to assess sampling uncertainty. Together, these enable reliable and robust assessments of disparities—an important tool when disparity assessment can have far-reaching policy implications. We demonstrate this in two case studies with real data: mortgage lending and personalized medicine dosing.
This paper was accepted by Hamid Nazerzadeh, Management Science Special Section on Data-Driven Prescriptive Analytics.
This article analyses main trends in the study of Ukrainian surnames from the period between the late seventeenth and the early twenty-first centuries. It points out the topicality of research on ...regional anthroponymy and its contribution to the development of studies on dialects, lexis, word formation and other issues in linguistics. Proper names contain a wealth of linguistic and historical information on realities of a nation or a particular region. The analysed material demonstrates that scholars investigating Ukrainian surnames have devoted considerable attention to the formation and development of the Ukrainian anthroponymic system, the functioning of anthroponyms in language, and the origin and semantics of personal names. They have identified the main stages in the formation of Ukrainian surnames and outlined the development of their role as a sign common to all members of a family, focusing in particular on the processes that have fostered the formation and development of the Ukrainian surname system. They have also examined the lexical basis of surnames, and identified the most productive lexical groups in this regard. The article presents the state of research on the classification of Ukrainian surnames according to their motivation features and means of their formation. It also sketches the prospects of further studies on Ukrainian anthroponomy. It points out that as yet there is no full register of Ukrainian surnames, and that some of the materials collected in particular regions have only been presented in dissertations and are often kept in private files of the researchers.
Objective. To efficiently estimate race/ethnicity using administrative records to facilitate health care organizations' efforts to address disparities when self‐reported race/ethnicity data are ...unavailable.
Data Source. Surname, geocoded residential address, and self‐reported race/ethnicity from 1,973,362 enrollees of a national health plan.
Study Design. We compare the accuracy of a Bayesian approach to combining surname and geocoded information to estimate race/ethnicity to two other indirect methods: a non‐Bayesian method that combines surname and geocoded information and geocoded information alone. We assess accuracy with respect to estimating (1) individual race/ethnicity and (2) overall racial/ethnic prevalence in a population.
Principal Findings. The Bayesian approach was 74 percent more efficient than geocoding alone in estimating individual race/ethnicity and 56 percent more efficient in estimating the prevalence of racial/ethnic groups, outperforming the non‐Bayesian hybrid on both measures. The non‐Bayesian hybrid was more efficient than geocoding alone in estimating individual race/ethnicity but less efficient with respect to prevalence (p<.05 for all differences).
Conclusions. The Bayesian Surname and Geocoding (BSG) method presented here efficiently integrates administrative data, substantially improving upon what is possible with a single source or from other hybrid methods; it offers a powerful tool that can help health care organizations address disparities until self‐reported race/ethnicity data are available.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
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