Suchergebnisse

The classification of Homo sapiens into varieties was a feature of eighteenth-century natural history. At this time living things were classified into genera, species, & varieties; the word race was used in the vernaculars in the sense of lineage. The eighteenth-century theory of African inferiority is to be found not in the works of intellectuals but in a popular literature that attributed African backwardness to the African environment. A serious confusion was originated by Baron Cuvier when, in 1817, he used race as a synonym for species. Cuvier's theory that the three great races had not changed since the last great natural catastrophe was the source for the theory of racial typology that became popular during the years 1848-1855. This theory maintained that racial types were suited to their historical environments & could not acclimatize to new ones; imperialism was therefore folly. By the late 1850s the confusions associated with racial classification were even greater. The idea nevertheless gained popularity because: (1) it became associated with that of nation & was useful in a nationalistic era; & (2) evolutionary thought was gathering strength & it appeared as if races might be implicated in evolutionary change. 3 Illustrations, 26 References. Modified AA

With the advent of the Internet of Things, scientists expect that the relationship between humans and motor vehicles will become integrated with information and communications technology to a greater extent. We examined the developmental stages of human‐vehicle interaction (HVI)
in the automobile industry and the changes in the relationship between humans and the motor vehicle. In this study we have provided a set of guidelines that enables the designer to classify goods and services applicable to an automobile based on socio-behavioral evaluation. To support this,
we analyzed driving tasks and conducted a focus group interview with 39 people to determine their inherent demands related to motor vehicles. We identified 3 stages of HVI: driver-centric, user-centric, and customer-centric.

Given the pervasiveness of employee silence, this article explores different forms of employee silence and silence antecedents. In particular, this article classifies employee silence using two dimensions: the target's solicitation and the employee's decision basis of conscious silence desirability. Drawing on relevant literature, it is proposed that employee silence can be classified into three distinct forms: unsolicited predetermined employee silence, unsolicited issue-based employee silence, and solicited target-based employee silence. When considering antecedents of employee silence, we claim that unsolicited predetermined employee silence is an outcome of personality traits, that unsolicited issue-based employee silence is triggered by functional motives, and that solicited target-based employee silence is determined by social relationships and relational experiences. By investigating forms of employee silence, this article provides important implications for theory and managerial practice.

AbstractThis article examines the symbolic order of the relationships between various social groups in disadvantaged neighborhoods and shows that ethnicity is the main reference point of derogatory designations or 'negative classifications'. Using two districts in German cities as examples, the semantic patterns of mutual negative classifications among autochthonous individuals and their Turkish neighbors are reconstructed. Upwardly mobile individuals of Turkish origin are the most frequent targets of stigmatization. This fact is explained by the existence of a deep symbolic dimension of social inequality that conceives of ethnicity in terms of kinship relations. The socially inclusive or exclusive effects of negative interethnic classifications and the related classification struggles depend on three factors: the internal, i.e. gradual or categorical logic of the classification patterns; the form and process of conflict resolution; and the social contexts in which negative classifications are used. While the disintegrating effects of negative classifications are curbed by institutionalized norms in local politics and economic life, there only exist informal performative norms of interaction in the life‐world, and here these classifications can more easily lead to social exclusion and ethnic separation.

The research of Human rights, their genesis, social roots has always been and remains an important problem during the mankind's historical development and continues to be the political, legal, or philosophical subject of the research. Human rights are being formed and developed with the development of mankind. The first codified laws, which include human rights norms, "Laws of Hammurabi", were established as early as 4000 years ago. It consisted of 282 laws and law was an unprecedented phenomenon in the ancient period of law artifacts, it is also considered to be the first version of the Code and contains the human rights norms.From the principles and purposes of the laws of Hammurabi, it is expressed that human rights do not have anything in common with the content of the present human rights, but the existence of these laws played a major role in the development of the justice system. From the beginning, they were the development, refinement, improvement and harmonization of the justice acts during the human history. Human rights have an important place in the international treaties and conventions.

In this special issue of Historical Social Research markets are considered as observable constellations of exchange and competition structured by classification and valuation procedures. Such a classification perspective on markets not only links the economy to culture by highlighting the role of a cognitive order for the engagement in economic action, but it also clarifies the moral character of markets. The introduction to this HSR Special Issue contextualizes this market perspective by first placing it in relation to disciplinary discontinuities in the sociological study of the economy, by outlining its new topicality arising from digital technologies, by discussing principal limitations or fallacies of classifications and measurements and, finally, by introducing the contributions of this special issue.

European inequality research often follows the tradition of using occupational based categorical classification to identify the socioeconomic position of individuals or households (e.g., classes, strata, milieus, occupational groups). In the past, European studies have often used the Erikson-Goldthorpe-Portocarero class (EGP) scheme (cf. Erikson & Goldthorpe 1992). However, the EGP scheme has only been validated for Great Britain (cf. Evans 1992). Variants for other countries are largely based on informed plausibility, following the British model, though operationalisation may vary by country. As an alternative to the EGP, two other currently available categorical concepts are the ESeC (European Socioeconomic Classification) and the ESeG (European Socioeconomic Groups), both based on the International Standard Classification of Occupation (ISCO). Both concepts are intended to improve cross-country comparative analysis of social inequality in Europe. However, the ESeC and ESeG differ in their theoretical basis and should not be confused with each other, and the ESeC and ESeG also cannot readily be transferred into each other. The ESeC is available for ISCO-88 (ESeC88) and ISCO-08 (ESeC08). The ESeG is available for ISCO-08. In this paper, we focus on the operationalisation of ESeC with EU-SILC cross-sectional data (2004-2020). Alongside this report, we have published syntax files (SPSS, Stata, and R) which can be used for the operationalisation of ESeC and ESeG.

This edited volume lays the groundwork for Social Data Science, addressing epistemological issues, methods, technologies, software and applications of data science in the social sciences. It presents data science techniques for the collection, analysis and use of both online and offline new (big) data in social research and related applications. Among others, the individual contributions cover topics like social media, learning analytics, clustering, statistical literacy, recurrence analysis and network analysis. Data science is a multidisciplinary approach based mainly on the methods of statistics and computer science, and its aim is to develop appropriate methodologies for forecasting and decision-making in response to an increasingly complex reality often characterized by large amounts of data (big data) of various types (numeric, ordinal and nominal variables, symbolic data, texts, images, data streams, multi-way data, social networks etc.) and from diverse sources. This book presents selected papers from the international conference on Data Science & Social Research, held in Naples, Italy in February 2016, and will appeal to researchers in the social sciences working in academia as well as in statistical institutes and offices.--

Résumé Actuellement dépassée, la traditionnelle distinction entre opposition qui a vocation à gouverner et opposition qui n'a pas vocation à gouverner a laissé place à une triple typologie : partis de gouvernement, formations de complément et opposition sociale. Si des rapprochements ponctuels peuvent advenir entre ces trois catégories, elles se distinguent nettement, aussi bien par leurs objectifs que par leurs moyens d'expression et d'action. Le devenir de l'opposition sociale reste cependant suspendu à sa capacité à se structurer et à dépasser son caractère conjoncturel.