Integrating professional socialization and training for sociology graduate students

It is a curious contradiction that sociology, a discipline that includes in its subject matter socialization, norms, occupations, formal organization, the institution of education and the concept of the career does not necessarily prepare its products in a systematic and coherent manner to become trained professionals. Newly minted Ph.D.s must often learn by trial and error because we have left them adrift concerning how to conduct themselves as professional sociologists. Moreover, while these new Ph.D.s are usually trained well as scholarly researchers, many are not prepared for the non-research careers they will take as sociologists. When this happens, we sociologists, supposedly enlightened about such matters, have failed our students. This article is divided into two parts. The first is a critique of traditional graduate education in sociology. The second part plays off these criticisms by offering a coherent plan, consonant with the current and future possibilities for sociologists.     

The influence of anthropogenic resources on multi-scale habitat selection by raccoons

With the continuing spread of urban areas, gaining a greater understanding of the effect of human presence on wildlife species is essential for wildlife managers. We determined the influence of anthropogenic resources on home range size and habitat selection of raccoons (Procyon lotor) during summer (June–August) 1996–2000 for 120 raccoons at three sites exposed to varying levels of urbanization and anthropogenic resources, specifically food. Home range estimates were larger (P < 0.05) at the rural site than the suburban and urban sites for both genders. We used compositional analysis to examine raccoon habitat selection at the second-order home range, second-order core area, and third-order home range scales. Woodland was consistently a highly-selected habitat type for both sexes at every spatial scale. Relative to other habitat types, habitat associated with human-related food (human use areas) was selected most often at the urban site, intermediately at the suburban site, and not selected at the rural site. Spatial scale also affected habitat selection. Human use areas were preferentially selected at the second- and third-order level at the urban site, third-order level only at the suburban site, and at neither level at the rural site. Additionally, intersexual differences in habitat selection were reduced at the urban site, with both sexes preferentially selecting for human use areas as well as woodland habitat. Smaller home ranges in urbanized environments are often attributed to the abundant and concentrated anthropogenic resources associated with human activity, but with little empirical support. Our habitat selection analyses followed our predictions that raccoon foraging is strongly influenced by the artificial distribution and abundance of human-related food. Male and female raccoons in urban areas reduce their foraging patterns and focus their foraging activity on anthropogenic foods.     

Some New Regression Methods for Predictive and Construct Validation

Social Indicators Research -     

Online interval scheduling: randomized and multiprocessor cases

We consider the problem of scheduling a set of equal-length intervals arriving online, where each interval is associated with a weight and the objective is to maximize the total weight of completed intervals. An optimal 4-competitive algorithm has long been known in the deterministic case, but the randomized case remains open. We give the first randomized algorithm for this problem, achieving a competitive ratio of 3.5822. We also prove a randomized lower bound of 4/3, which is an improvement over the previous 5/4 result. Then we show that the techniques can be carried to the deterministic multiprocessor case, giving a 3.5822-competitive 2-processor algorithm, and a 4/3 lower bound for any number of processors. We also give a lower bound of 2 for the case of two processors. A preliminary version of this paper appeared in the Proceedings of COCOON 2007, LNCS, vol. 4598, pp. 176–186. The work described in this paper was fully supported by a grant from City University of Hong Kong (SRG 7001969), and NSFC Grant No. 70525004 and 70702030.     

An Integrated Approach for Assessing the Impact of Large-Scale Future Floods on a Highway Transport System

The negative impact of climate change continues to escalate flood risk. Floods directly and indirectly damage highway systems and disturb the socioeconomic order. In this study, we propose an integrated approach to quantitatively assess how floods impact the functioning of a highway system. The approach has three parts: (1) a multi-agent simulation model to represent traffic, heterogeneous user demand, and route choice in a highway network; (2) a flood simulator using future runoff scenarios generated from five global climate models, three representative concentration pathways (RCPs), and the CaMa-Flood model; and (3) an impact analyzer, which superimposes the simulated floods on the highway traffic simulation system, and quantifies the flood impact on a highway system based on car following model. This approach is illustrated with a case study of the Chinese highway network. The results show that (i) for different global climate models, the associated flood damage to a highway system is not linearly correlated with the forcing levels of RCPs, or with future years; (ii) floods in different years have variable impacts on regional connectivity; and (iii) extreme flood impacts can cause huge damages in highway networks; that is, in 2030, the estimated 84.5% of routes between provinces cannot be completed when the highway system is disturbed by a future major flood. These results have critical implications for transport sector policies and can be used to guide highway design and infrastructure protection. The approach can be extended to analyze other networks with spatial vulnerability, and it is an effective quantitative tool for reducing systemic disaster risk.     

Fast searching games on graphs

Given a graph, suppose that intruders hide on vertices or along edges of the graph. The fast searching problem is to find the minimum number of searchers required to capture all the intruders satisfying the constraint that every edge is traversed exactly once and searchers are not allowed to jump. In this paper, we prove lower bounds on the fast search number. We present a linear time algorithm to compute the fast search number of Halin graphs and their extensions. We present a quadratic time algorithm to compute the fast search number of cubic graphs.     

Historic Preservation in Czechoslovakia: The Chȃteau at Staré Hrady

The paper discusses the gendering of the Lithuanian national movement during its formative stage, 1883–1914. It concentrates on the intelligentsia’s debate on the women’s question, which served as one of the most significant cultural battlegrounds for the national elite, helping to define its own identity and new directions for Lithuanian nationalism. Through the discussion of different marital strategies and women’s roles in national politics as seen by the male intelligentsia, the paper argues that, despite the harsh critique of traditional peasant gender relations, the debate amounted to women’s virtual domestication. For male patriots, the emancipation of Lithuanian women meant, first of all, accepting the role of patriotic wives, i.e., responsibility for the education of children, or the role of nation mothers, which entailed nurturing new members of the community. A few secular and independent women writers were welcomed into nation-building politics but only as junior partners.     

The Christian difference: Surviving postmodernism

Abstract

Drawing on the work of Nicholas Boyle, this paper argues that postmodernism represents the intellectual style we should expect as part of developing global capitalist regimes. Accordingly, I argue that postmodernism is not a friend but an enemy to Christianity just to the extent the former tempts us to lose our history. In that respect, the challenge of postmodernism is no different than the challenge of modernity. It becomes the Christian task now to narrate modernity and postmodernity on our own terms rather than those offered by the postmodernists. But for Christianity to be capable of such narration, it must rediscover in its own life the significance of the church which is capable of surviving in a world which is in many ways quite accurately described as postmodern.     

The Role of Topic Interest in Survey Participation Decisions

While a low survey response rate may indicate that the riskof nonresponse error is high, we know little about when nonresponsecauses such error and when nonresponse is ignorable. Leverage-saliencetheory of survey participation suggests that when the surveytopic is a factor in the decision to participate, noncooperationwill cause nonresponse error. We test three hypotheses derivedfrom the theory: (1) those faced with a survey request on atopic of interest to them cooperate at higher rates than dothose less interested in the topic; (2) this tendency for the"interested" to cooperate more readily is diminished when monetaryincentives are offered; and (3) the impact of interest on cooperationhas nonignorability implications for key statistics. The datacome from a three-factor experiment examining the impact oncooperation with surveys on (a) five different topics, using(b) samples from five different populations that have knownattributes related to the topics, with (c) two different incentiveconditions.     

Evaluating Population Forecast Accuracy: A Regression Approach Using County Data

Many studies have evaluated the impact of differences in population size and growth rate on population forecast accuracy. Virtually all these studies have been based on aggregate data; that is, they focused on average errors for places with particular size or growth rate characteristics. In this study, we take a different approach by investigating forecast accuracy using regression models based on data for individual places. Using decennial census data from 1900 to 2000 for 2,482 counties in the US, we construct a large number of county population forecasts and calculate forecast errors for 10- and 20-year horizons. Then, we develop and evaluate several alternative functional forms of regression models relating population size and growth rate to forecast accuracy; investigate the impact of adding several other explanatory variables; and estimate the relative contributions of each variable to the discriminatory power of the models. Our results confirm several findings reported in previous studies but uncover several new findings as well. We believe regression models based on data for individual places provide powerful but under-utilized tools for investigating the determinants of population forecast accuracy.