Overcoming the Effects of Variation in Infant Speech Segmentation: Influences of Word Familiarity

Previous studies have shown that 7.5‐month‐olds can track and encode words in fluent speech, but they fail to equate instances of a word that contrast in talker gender, vocal affect, and fundamental frequency. By 10.5 months, they succeed at generalizing across such variability, marking a clear transition period during which infants' word recognition skills become qualitatively more mature. Here we explore the role of word familiarity in this critical transition and, in particular, whether words that occur frequently in a child's listening environment (i.e., “Mommy” and “Daddy”) are more easily recognized when they differ in surface characteristics than those that infants have not previously encountered (termed nonwords). Results demonstrate that words are segmented from continuous speech in a more linguistically mature fashion than nonwords at 7.5 months, but at 10.5 months, both words and nonwords are segmented in a relatively mature fashion. These findings suggest that early word recognition is facilitated in cases where infants have had significant exposure to items, but at later stages, infants are able to segment items regardless of their presumed familiarity.     

Consumption and Saving Behavior of Older and Younger Baby Boomers in Korea

The 1998 Korean Survey of Family Income and Expenditures was used to examine the overall consumption and saving behavior of Korean baby boomers and compared the differences in consumption and saving behavior between older and younger boomers. The t -test results indicated that the younger boomers allocated a significantly higher percentage of their expenditures on food away from home, household appliances, transportation and communication than did the older boomers, whereas the older boomers spent higher amounts and allocated larger budget shares on their children's education than did the younger boomers. The results of Ordinary Least-Squares (OLS) regression analysis showed that, holding other factors constant, older boomers not only spent significantly more in the total consumption expenditures and education expenditures, but older boomers also saved significantly less than did younger boomers.     

The Gendered Face of Terrorism

What does sociology have to contribute to our understanding of terrorism? As scholars of gender and the Far Right, we believe that we have much to offer the current debates. In this article, we focus both on contemporary cases of terrorism, the attacks of September 11 and the Oklahoma City bombing, and terrorist movements as gendered: as enactments of masculinity. In particular, we focus on the contemporary white supremacist movement, the most dangerous domestic terrorist threat faced by the USA. We suggest that the ideology and organization of many terrorist groups are saturated with gendered meanings, both as the analytic prism through which they view their situation, and also as a means of political mobilization.     

Privatization of refuse removal and labor costs

We examine the labor-cost savings associated with privatization by comparing earnings and employment trends of public and private sector refuse workers. Findings suggest that high union earnings for workers in the public sector are a source of labor-cost savings in the refuse industry. Evidence on job changers does not indicate that earnings for this group of workers are a compensating differential. Metropolitan area employment findings suggest that municipalities are less likely to use union refuse workers in the public sector when a relatively small percentage of area residents belong to a union. The authors thank Jacqueline Agesa, Keith Bender, Maria Crawford, and Richard Perlman for valuable suggestions. Research assistance from Eric Blackburn is greatly appreciated.     

Choice of the primary analysis in longitudinal clinical trials

Missing data, and the bias they can cause, are an almost ever‐present concern in clinical trials. The last observation carried forward (LOCF) approach has been frequently utilized to handle missing data in clinical trials, and is often specified in conjunction with analysis of variance (LOCF ANOVA) for the primary analysis. Considerable advances in statistical methodology, and in our ability to implement these methods, have been made in recent years. Likelihood‐based, mixed‐effects model approaches implemented under the missing at random (MAR) framework are now easy to implement, and are commonly used to analyse clinical trial data. Furthermore, such approaches are more robust to the biases from missing data, and provide better control of Type I and Type II errors than LOCF ANOVA. Empirical research and analytic proof have demonstrated that the behaviour of LOCF is uncertain, and in many situations it has not been conservative. Using LOCF as a composite measure of safety, tolerability and efficacy can lead to erroneous conclusions regarding the effectiveness of a drug. This approach also violates the fundamental basis of statistics as it involves testing an outcome that is not a physical parameter of the population, but rather a quantity that can be influenced by investigator behaviour, trial design, etc. Practice should shift away from using LOCF ANOVA as the primary analysis and focus on likelihood‐based, mixed‐effects model approaches developed under the MAR framework, with missing not at random methods used to assess robustness of the primary analysis. Copyright © 2004 John Wiley & Sons, Ltd.     

Markov chain Monte Carlo methods for high dimensional inversion in remote sensing

Summary.  We discuss the inversion of the gas profiles (ozone, NO₃, NO₂, aerosols and neutral density) in the upper atmosphere from the spectral occultation measurements. The data are produced by the 'Global ozone monitoring of occultation of stars' instrument on board the Envisat satellite that was launched in March 2002. The instrument measures the attenuation of light spectra at various horizontal paths from about 100 km down to 10–20 km. The new feature is that these data allow the inversion of the gas concentration height profiles. A short introduction is given to the present operational data management procedure with examples of the first real data inversion. Several solution options for a more comprehensive statistical inversion are presented. A direct inversion leads to a non-linear model with hundreds of parameters to be estimated. The problem is solved with an adaptive single-step Markov chain Monte Carlo algorithm. Another approach is to divide the problem into several non-linear smaller dimensional problems, to run parallel adaptive Markov chain Monte Carlo chains for them and to solve the gas profiles in repetitive linear steps. The effect of grid size is discussed, and we present how the prior regularization takes the grid size into account in a way that effectively leads to a grid-independent inversion.