Do Infants Recognize Engagement in Social Interactions? The Case of Face‐to‐Face Conversation

This study explores 12‐month‐olds' understanding of face‐to‐face conversation, a key contextual structure associated with engagement in a social interaction. Using a violation‐of‐expectations paradigm, we habituated infants to a “face‐to‐face” conversation, and in a test phase compared their looking times between “back‐to‐back” (conceptually novel) and “face‐to‐face” (conceptually familiar) conversations, while simultaneously manipulating perceptual familiarity in a 2 × 2 factorial design. We also analyzed dynamic changes in pupil dilation, which are considered a reliable measure of cognitive load that may index processing of social interactions. Infants looked relatively longer at perceptual changes (new speaker positions) but not at conceptual change (back‐to‐back conversation), suggesting that face‐to‐face conversation may not elicit particular expectations, and so may not carry any particular conceptual significance. Moreover, on the first test trial, larger pupil dilation was observed for familiar conditions, suggesting that familiarity with perceptual features could enhance processing of conversations. Thus, this study undermines assertions regarding infants' conceptual understanding of the social signals underlying engagement. Infants may rather recognize such signals through their perceptual familiarity and associated positive feelings. This may then increase their engagement when observing and participating in others' collaborative activities, in turn allowing for the development of knowledge regarding others' intentions.     

Characterizing the Performance of the Conway‐Maxwell Poisson Generalized Linear Model

Count data are pervasive in many areas of risk analysis; deaths, adverse health outcomes, infrastructure system failures, and traffic accidents are all recorded as count events, for example. Risk analysts often wish to estimate the probability distribution for the number of discrete events as part of doing a risk assessment. Traditional count data regression models of the type often used in risk assessment for this problem suffer from limitations due to the assumed variance structure. A more flexible model based on the Conway‐Maxwell Poisson (COM‐Poisson) distribution was recently proposed, a model that has the potential to overcome the limitations of the traditional model. However, the statistical performance of this new model has not yet been fully characterized. This article assesses the performance of a maximum likelihood estimation method for fitting the COM‐Poisson generalized linear model (GLM). The objectives of this article are to (1) characterize the parameter estimation accuracy of the MLE implementation of the COM‐Poisson GLM, and (2) estimate the prediction accuracy of the COM‐Poisson GLM using simulated data sets. The results of the study indicate that the COM‐Poisson GLM is flexible enough to model under‐, equi‐, and overdispersed data sets with different sample mean values. The results also show that the COM‐Poisson GLM yields accurate parameter estimates. The COM‐Poisson GLM provides a promising and flexible approach for performing count data regression.     

DYNAMICAL AND STATISTICAL MODELS FOR EXPLOITED POPULATIONS†

Human activities have indirectly modified the dynamics of many populations, accelerating considerably the natural rate of species extinction and raising strong concerns about biodiversity. In many such cases, the underlying ‘natural’ dynamics of the population has been modified by human‐induced increases in mortality, even if the populations are not exploited or harvested in the strict sense. Both dynamical and statistical models are needed to investigate the consequences of human‐induced mortality on the overall dynamics of a population. This paper reviews existing approaches and the potential of recent developments to help form a conceptual and practical framework for analysing the dynamics of exploited populations. It examines both the simple case of an extra source of mortality instantaneously in time, and the theory involved when both risks compete over a continuous time scale. This basic theory is expanded to structured populations, using matrix population models, with applications to the conservation biology of long‐lived vertebrates. The type and degree of compensation expected and approaches to detect it are reviewed, and ways of handling uncertainty are discussed.     

Comment confronter mobilité « subjective » et mobilité « objective » ?

The methods for analyzing objective social mobility and subjective mobility as perceived by individuals are reviewed in the case of two surveys: Trois générations by the French Old-Age Fund (CNAV, Caisse Nationale d'Assurance Vieillesse) and Formation qualification professionnelle by the French National Institute of Statistics and Economic Studies (INSEE). These two surveys have formulated subjective mobility in quite different ways, but this observation also holds for objective mobility, which, for the purpose of comparison with respondents' subjective evaluations, is defined using specific procedures. A method is proposed for contrasting these two sorts of mobility based on classical mobility tables. When the latter are designed so as to cross three variables (social origins, destinations and average scores of subjective mobility), the spontaneous sociology that can be collectively detected in the assessments made by respondents turns out to be not very different from the scholarly sociology of social categories produced by sociologists. After showing that subjective and objective mobility vary coherently in relation to each other, an additional hypothesis is advanced to account for some discrepancies.     

Statistical analysis of rank data from a visual matching of colored textures

Nowadays, sensory properties of materials are subject to growing attention both in an hedonic point of view and in an utilitarian one. Hence, the formulation of the foundations of an instrumental metrological approach that will allow for the characterization of visual similarities between textures belonging to the same type becomes a challenge of the research activities in the domain of perception. In this paper, our specific objective is to link an instrumental approach of metrology of the assessment of visual textures with a metrology approach based on a softcopy experiment performed by human judges. The experiment consisted in ranking of isochromatic colored textures according to the visual contrast. A fixed effects additive model is considered for the analysis of the rank data collected from the softcopy experiment. The model is fitted to the data using a least-squares criterion. The resulting data analysis gives rise to a sensory scale that shows a non-linear correlation and a monotonic functional relationship with the physical attribute on which the ranking experiment is based. Furthermore, the capacity of the judges to discriminate the textures according to the visual contrast varies according to the color ranges and the textures types.     

Le syndicat des travailleurs domestiques de Rio de Janeiro : un observatoire des transformations de l'emploi domestique au Brésil

This study of the major dimensions of actions undertaken by the labor union for household employees in Rio de Janeiro shows how the new “social rights” extended to these personal service workers has led to a new sense of what is “fair” and to an increase in lawsuits with employers. Given its place in labor relations courts, the union's position is ambivalent. Light is shed on the tensions between various categories of persons who visit the union's offices — tensions that tell us much about social relations. Attention is then turned to this small organization's role in labor courts: after cases have been heard, household employees often have a feeling that their rights have been upheld.     

Work and pay in flexible and regulated labor markets: A generalized perspective on institutional evolution and inequality trends in Europe and the U.S.

In recent years a “unified theory” has emerged out of labor economics, which argues that a combination of “macroeconomic shocks” and flexible labor market institutions in the U.S. has produced strong upward trends in wage inequality, while these same shocks have produced high unemployment and low employment growth in Europe as a side effect of the wage stability preserved by that continent's rigid labor market institutions. This paper takes issue with the common view that inequality trends are best explained by a model of stable institutions interacting with changing macroeconomic forces. It argues that European institutions in fact have changed, and that institutional changes which were triggered by the broader macroeconomic forces have affected the form as well as the size of inequality trends. While the U.S. has experienced rising strong skill-based wage inequality, institutional change in France has produced an upward trend in the density of insecure jobs and an increased concentration of low-skill workers in insecure jobs. These results challenge the view that low employment rates is the sole mechanism through which European labor markets have absorbed asymmetric shocks to their demand for labor.     

ON LIKELIHOOD ESTIMATION FOR DISCRETELY OBSERVED MARKOV JUMP PROCESSES

The parameter estimation problem for a Markov jump process sampled at equidistant time points is considered here. Unlike the diffusion case where a closed form of the likelihood function is usually unavailable, here an explicit expansion of the likelihood function of the sampled chain is provided. Under suitable ergodicity conditions on the jump process, the consistency and the asymptotic normality of the likelihood estimator are established as the observation period tends to infinity. Simulation experiments are conducted to demonstrate the computational facility of the method.     

A Time-Series Study of the Formation and Predictive Performance of EEC Production Survey Expectations

Generalized method of moments (GMM) has been an important innovation in econometrics. Its usefulness has motivated a search for good inference procedures based on GMM. This article presents a novel method of bootstrapping for GMM based on resampling from the empirical likelihood distribution that imposes the moment restrictions. We show that this approach yields a large-sample improvement and is efficient, and give examples. We also discuss the development of GMM and other recent work on improved inference.