Distributional Phonetic Learning at 10 Months of Age

Infant phonetic perception reorganizes in accordance with the native language by 10 months of age. One mechanism that may underlie this perceptual change is distributional learning, a statistical analysis of the distributional frequency of speech sounds. Previous distributional learning studies have tested infants of 6–8 months, an age at which native phonetic categories have not yet developed. Here, three experiments test infants of 10 months to help illuminate perceptual ability following perceptual reorganization. English‐learning infants did not change discrimination in response to nonnative speech sound distributions from either a voicing distinction (Experiment 1) or a place‐of‐articulation distinction (Experiment 2). In Experiment 3, familiarization to the place‐of‐articulation distinction was doubled to increase the amount of exposure, and in this case infants began discriminating the sounds. These results extend the processes of distributional learning to a new phonetic contrast, and reveal that at 10 months of age, distributional phonetic learning remains effective, but is more difficult than before perceptual reorganization.     

The Sociology of Political Representation and Deliberation

The language of democracy and citizenship is infused with a complicated idea: political representation. While political theorists have explored what representation and deliberation should be like, most research on how political discussion actually happens fails directly to address these theoretical standards. This article shows the importance of representation and deliberation to our contemporary ideas about democracy and citizenship. It shows that there is no clear line between deliberation and everyday conversation. Instead, everyday talk constitutes the foundation on top of which citizens build ideas about politics. These, in turn, are the bedrock of democratic representation.     

Behavioral complexity in leadership: The psychometric properties of a new instrument to measure behavioral repertoire

Research in managerial and executive leadership recognizes the importance of behavioral complexity, particularly for addressing the competing demands and roles expected of managerial leaders. Though some empirical research on behavioral complexity exists, further progress requires a more rigorous instrument to measure behavioral repertoire. We design an elaborated, multi-dimensional instrument based on the Competing Values Framework (CVF). To examine the underlying conceptual structure and remove measurement error, we test this second-order measurement model using structural equation modeling (SEM). We also test the spatial relationship of the factors using a Bayesian circumplex model. Our data largely support the theoretical structure and stringent demands of the CVF model as applied to this instrument. Finally, we test the instrument's ability to predict managerial effectiveness and find that higher overall ability is correlated with greater overall performance. With this new instrument, we suggest the modification and addition of roles associated with the CVF model.     

ECONOMIC GROWTH REGRESSIONS FOR THE AMERICAN STATES: A SENSITIVITY ANALYSIS

We use extreme-bounds analysis to assess the sensitivity of numerous control variables identified in the state growth literature. We employ annual panel data on the American states to identify which variables are robust to small changes in the conditioning information set. The results provide a set of core variables as a starting point for future research that relies on state growth regressions. The findings also demonstrate that several important conclusions in the literature depend on how variables are measured. ( JEL R11, O23, C23, 018)     

Past and new victimization among African American female drug users who participated in an HIV risk-reduction intervention

This study examined to what extent a women- and culturally-specific sexual risk reduction intervention resulted in a decline of new victimization intervention. Additionally, we sought to identify factors associated with new victimization, defined as victimization during the 6 months after enrollment in the study. Female African American drug users (N = 333, ages 18-59 years) completed questionnaires. Past victimization was a major predictor of new victimization. The likelihood of new victimization, however, declined significantly when compared to past victimization. Factors associated with victimization included enhanced intervention assignment, frequency of drug use, lifestyle factors such as criminal behavior, drug use in a public setting, and living in an unstable situation. Results indicate the need to incorporate strategies to reduce victimization in HIV/AIDS and other health-related prevention and intervention programs.     

"Just trying to relax": masculinity,masculinizing practices,and strip club regulars

This article explores customers' understandings of their visits to heterosexual strip clubs and the ways in which those visits become meaningful to them in relation to cultural discourses around masculinity, sexuality, leisure, and consumption, as well as in relation to their everyday lives and relationships. Not every man finds strip clubs pleasurable, yet understanding why some men frequent these venues can inform us more generally about the links between sexuality, gender, and the marketplace. This article focuses on regular male customers' stated motives for visiting strip clubs and examines those visits as touristic and masculinizing practices. It also explores gender, sexuality, and power in the men s performances of desire in the clubs, taking up issues of visibility, virility, youthfulness, and commodification.     

Nonparametric confidence regions via the analytic wild bootstrap

The wild bootstrap is a nonparametric tool that can be used to estimate a sampling distribution in the presence of heteroscedastic errors. In particular, the wild bootstrap enables us to compute confidence regions for regression parameters under non-i.i.d. models. While the wild bootstrap may perform well in these settings, its obvious drawback is a lack of computational efficiency. The wild bootstrap requires a large number of bootstrap replications, making the use of this tool impractical when dealing with big data. We introduce the analytic wild bootstrap (ANWB), which provides a nonparametric alternative way of constructing confidence regions for regression parameters. The ANWB is superior to the wild bootstrap from a computational standpoint while exhibiting similar finite-sample performance. We report simulation results for both least squares and ridge regression. Additionally, we test the ANWB on a real dataset and compare its performance with that of other standard approaches.     

Revising Infant Mortality Rates for the Early Twentieth Century United States

Accurate vital statistics are required to understand the evolution of racial disparities in infant health and the causes of rapid secular decline in infant mortality during the early twentieth century. Unfortunately, U.S. infant mortality rates prior to 1950 suffer from an upward bias stemming from a severe underregistration of births. At one extreme, African American births in southern states went unregistered at the rate of 15 % to 25 %. In this study, we construct improved estimates of births and infant mortality in the United States for 1915–1940 using recently released complete count decennial census microdata combined with the counts of infant deaths from published sources. We check the veracity of our estimates with a major birth registration study completed in conjunction with the 1940 decennial census and find that the largest adjustments occur in states with less-complete birth registration systems. An additional advantage of our census-based estimation method is the extension backward of the birth and infant mortality series for years prior to published estimates of registered births, enabling previously impossible comparisons and estimations. Finally, we show that underregistration can bias effect estimates even in a panel setting with specifications that include location fixed effects and place-specific linear time trends.