Suchergebnisse

We live in a world of big data: the amount of information collected on human behavior each day is staggering, and exponentially greater than at any time in the past. Additionally, powerful algorithms are capable of churning through seas of data to uncover patterns. Providing a simple and accessible introduction to data mining, Paul Attewell and David B. Monaghan discuss how data mining substantially differs from conventional statistical modeling familiar to most social scientists. The authors also empower social scientists to tap into these new resources and incorporate data mining methodologi

Outlining the world-wide race for educational advantage, this book takes a comparative approach. Covering almost every continent, this book provides an overarching examination of who is actually able to benefit from economic growth and who, because of the educational demands it brings about, it shuts out.

Rates of involuntary job loss (from plant closures, downsizing, etc) have been increasing in the US during the past 15 years. Using several cross-sectional surveys from the Current Population Survey, & longitudinal data from the Panel Study of Income Dynamics, it is demonstrated here that the likelihood of job displacement differs according to marital status, the presence or absence of young children, & single parenthood, even after controlling for employees' age, sex, race, education, industry, occupation, & other pertinent factors. Divorce is associated with the subsequent job loss. Conversely, job displacement also raises the risk of subsequent marital breakdown. Findings indicating that the waves of job displacement have not been neutral with regard to family structure are discussed in terms of theories of work-family conflicts. 5 Tables, 28 References. Adapted from the source document.

The dominant explanation for the spread of technological innovations emphasizes processes of influence and information flow. Firms which are closely connected to pre-existing users of an innovation learn about it and adopt it early on. Firms at the periphery of communication networks are slower to adopt. This paper develops an alternative model which emphasizes the role of know-how and organizational learning as potential barriers to adoption of innovations. Firms delay in-house adoption of complex technology until they obtain sufficient technical know-how to implement and operate it successfully. In response to knowledge barriers, new institutions come into existence which progressively lower those barriers, and make it easier for firms to adopt and use the technology without extensive in-house expertise. Service bureaus, consultants, and simplification of the technology are examples. As knowledge barriers are lowered, diffusion speeds up, and one observes a transition from an early pattern in which the new technology is typically obtained as a service to a later pattern of in-house provision of the technology. Thus the diffusion of technology is reconceptualized in terms of organizational learning, skill development, and knowledge barriers. The utility of this approach is shown through an empirical study of the diffusion of business computing in the United States, reporting survey and ethnographic data on the spread of business computing, on the learning processes and skills required, and on the changing institutional practices that facilitated diffusion.

Abstract
For some, the history of clerical work epitomizes the way in which technological change and the division of labor result in the deskilling and degradation of work. This paper argues that this perception of clerical deskilling is mistaken, the result of an inaccurate portrayal of traditional clerking, and of a theoretical tendency to (mis)read declines in the prestige and pay of an occupation as stemming from changes in skill. Focusing on Victorian clerks' own descriptions of their work, and moving to the present period, the paper offers an alternative reading of clerical history and of the dynamics of occupational decline.

Abstract
This article examines the undergraduate major as a closure mechanism in occupations among college graduates, using the American Community Surveys. We measure the college major density of occupations, termed "major specialization", finding that greater major specialization of an occupation is associated with higher earnings, over and above previously identified closure devices (licensure, unionization, and vertical educational credentialing), and college selectivity. We conclude that major specialization operates as a powerful earnings-boosting closure device within higher-educated labor markets. Additional analyses regarding premiums from individuals matching their own college major with their occupation's typical major indicate comparatively small earnings payoffs. Hence, deviating from one's occupation's usual credential does not generate a substantial earnings penalty. Furthermore, payoffs from major-occupation matching have a ceiling: there is no further payoff above the average match level. These findings demonstrate how occupational closure theory helps explain the substantial earnings advantages of certain college majors in the labor force.