Social Background Differences in Early Family Behavior

Social background has historically been recognized as a major factor influencing family behavior, though recent work has largely emphasized racial/ethnic influences. Here we use 1994 – 1995 and 2001 – 2002 Add Health data to examine the cohabitation, first marriage, and first birth experience of young women. In a multistate life table context, hypothetical cohorts specified in terms of race and mother’s education are followed, from age 11 to age 24, as they move through 6 family‐related statuses. The results indicate that, for both Black and White women, a higher level of maternal education is generally associated with less cohabitation, less marriage, fewer first births, and a higher percentage of women who experience none of those transitions before age 24. Racial and social background differences are conceptually and empirically distinct. Because mother’s education is associated with substantially different trajectories of early family behavior for both Blacks and Whites, we argue that social background merits increased attention in research on contemporary American family patterns.     

FOR MONEY OR GLORY? COMMERCIALIZATION,COMPETITION, AND SECRECY IN THE ENTREPRENEURIAL UNIVERSITY

Scholars have grown concerned that the commercialization of academic science is increasing secrecy at the expense of cooperation and information sharing. Using data from comparable surveys of academic scientists in three fields (experimental biology, mathematics, and physics), we test whether scientists have become more competitive and more secretive over the last 30 years. We also use the recent survey to test a multivariate model of the effects of scientific competition and commercialization (patenting, industry funding, and industry collaboration) on scientific secrecy. We find that secrecy has increased, and has increased particularly for experimental biologists. Only 13 percent of experimental biologists in 1998 felt safe discussing their ongoing research with all others doing similar work. Our multivariate analysis shows that this secrecy is most related to concerns about being anticipated (scientific competition). We find that patenting is associated with increased secrecy among mathematicians and physicists, but not for experimental biologists. We find that industry funding is associated with more secrecy, while industry collaboration is associated with less secrecy, across fields. Our results suggest that the recent concern over increasing scientific secrecy has merit. However, this increased secrecy seems to result from a combination of increasing commercial linkages and increased pressures from scientific competition. Our research highlights the central role that scientists' competition for priority plays in the system of science and that, while such competition spurs effort, it also produces negative effects that recent trends toward commercialization of academic science seem to be exacerbating.     

Identity Dilemmas: Toward a More Situated Understanding

When are identity dilemmas—when people possess identities that conflict with one another and both are potentially stigmatizing—most likely to occur? Are they the result of generic social processes? A review of some of the extant research on “identity work” suggests that historical “misalignments” of culture and stratification, which we refer to as “lag,” create the greatest potential for stigma and the reproduction of inequalities. Lag is exacerbated by complex, intersecting axes of hierarchy, and amplified as symbolic environments globalize and subcultures multiply. Articulating culture and structure reveals how power plays out in interaction, and highlights the omnipresence of struggles for treatment as “fully human.” We consider whether “alignment” is even possible when multiple dimensions of social location intertwine, compete, and collide. Following Schwalbe and Mason‐Schrock (1996), we argue that “subcultural” or collective identity work that brings new meanings into dominant cultural narratives may offer the greatest hope, but in the interim all coping strategies are costly.     

A Bayesian Approach for Analyzing Results of Vehicle Collision Tests

Certain motor vehicle safety standards stipulate a collision test speed and a set of performance criteria that vehicles must satisfy during or after the collision test. For example, Federal Motor Vehicle Safety Standard 301 requires a 30 mile per hour (mph) barrier collision and specifies a certain maximum allowable limit on the total spillage of fuel. Vehicle designs are required to meet this standard; however, when collision tests are conducted at speeds higher than the standard, vehicles do not always satisfy the performance criteria. This paper develops a mathematical model for estimating the probability of meeting the standard by using a Bayesian framework to incorporate engineering judgment with collision test results. The model is based on the idea that there are random features to a vehicle's ability to meet performance standards in a collision, especially at such elevated speeds. Example calculations are included to illustrate the estimation of the probability of meeting the standard and to compare it with a maximum likelihood approach.     

On the Joint Lot-Sizing Problem with Zero Setup Costs

In a recent paper, Pinto and Mabert [5] presented a lot-sizing rule and an improvement procedure for the joint lot-sizing problem with zero setup costs. We show that this procedure often yields infeasible schedules. We also present and discuss two interesting properties of the joint lot-sizing problem with zero setup costs. A numerical example to illustrate the second property is provided.     

On the computation of the noncentral <Emphasis Type="Italic">F</Emphasis> and noncentral beta distribution

Unfortunately many of the numerous algorithms for computing the comulative distribution function (cdf) and noncentrality parameter of the noncentral F and beta distributions can produce completely incorrect results as demonstrated in the paper by examples. Existing algorithms are scrutinized and those parts that involve numerical difficulties are identified. As a result, a pseudo code is presented in which all the known numerical problems are resolved. This pseudo code can be easily implemented in programming language C or FORTRAN without understanding the complicated mathematical background. Symbolic evaluation of a finite and closed formula is proposed to compute exact cdf values. This approach makes it possible to check quickly and reliably the values returned by professional statistical packages over an extraordinarily wide parameter range without any programming knowledge. This research was motivated by the fact that a very useful table for calculating the size of detectable effects for ANOVA tables contains suspect values in the region of large noncentrality parameter values compared to the values obtained by Patnaik’s 2-moment central-F approximation. The cause is identified and the corrected form of the table for ANOVA purposes is given. The accuracy of the approximations to the noncentral-F distribution is also discussed. The authors wish to thank Mr. Richárd Király for his preliminary work. The authors are grateful to the Editor and Associate Editor of STCO and the unknown reviewers for their helpful suggestions.     

A framework for the comparison of maximum pseudo-likelihood and maximum likelihood estimation of exponential family random graph models

The statistical modeling of social network data is difficult due to the complex dependence structure of the tie variables. Statistical exponential families of distributions provide a flexible way to model such dependence. They enable the statistical characteristics of the network to be encapsulated within an exponential family random graph (ERG) model. For a long time, however, likelihood-based estimation was only feasible for ERG models assuming dyad independence. For more realistic and complex models inference has been based on the pseudo-likelihood. Recent advances in computational methods have made likelihood-based inference practical, and comparison of the different estimators possible.