Unexpected but authentic use of an ethnically–marked dialect

Recent work on language crossing in the U.S. has examined the temporary appropriation of African American Vernacular English by white youth in an effort to participate in the current popularity and prestige of hip–hop culture, or in order to highlight racial boundaries. While such verbal behavior probably encompasses most white use of AAVE, it is not the only way in which whites (or other non–blacks) can use the variety. This paper presents a case study of the language of a 23 year old white female who makes consistent use of many distinctive linguistic features associated with AAVE. I argue that the interaction of ideologies of race, class, localness and language allow her to be considered an ingroup member despite her biographical race. This suggests that there is a tension between academic linguistic theory and actual speaker practice in assigning authenticity to individuals, and I conclude that language ideologies and other forms of qualitative evidence should be taken into account by sociolinguists looking at the link between language and race.     

Infants' Responses to Gender‐Inconsistent Events

Toddlers' knowledge of the stereotyping of traditionally feminine and masculine household activities was examined using the preferential looking paradigm. Seventy‐seven 24‐month‐old infants observed a series of 9 pairs of photographs, each portraying a male and female adult engaged in the same stereotyped or gender‐neutral activity (e.g., ironing, hammering, or reading). Longer looking times were predicted on stimuli inconsistent with gender stereotypes (e.g., looking longer at the man putting on lipstick than at the woman). The results suggested that toddlers have acquired some knowledge of the gender stereotyping of feminine activities by their 2nd birthday.     

Goodness‐of‐fit methods for matched case‐control studies

The authors propose graphical and numerical methods for checking the adequacy of the logistic regression model for matched case‐control data. Their approach is based on the cumulative sum of residuals over the covariate or linear predictor. Under the assumed model, the cumulative residual process converges weakly to a centered Gaussian limit whose distribution can be approximated via computer simulation. The observed cumulative residual pattern can then be compared both visually and analytically to a certain number of simulated realizations of the approximate limiting process under the null hypothesis. The proposed techniques allow one to check the functional form of each covariate, the logistic link function as well as the overall model adequacy. The authors assess the performance of the proposed methods through simulation studies and illustrate them using data from a cardiovascular study.     

Domains of convergence for the EM algorithm: a cautionary tale in a location estimation problem

The EM algorithm is a popular method for maximizing a likelihood in the presence of incomplete data. When the likelihood has multiple local maxima, the parameter space can be partitioned into domains of convergence, one for each local maximum. In this paper we investigate these domains for the location family generated by the t-distribution. We show that, perhaps somewhat surprisingly, these domains need not be connected sets. As an extreme case we give an example of a domain which consists of an infinite union of disjoint open intervals. Thus the convergence behaviour of the EM algorithm can be quite sensitive to the starting point.     

TOWARD A SOCIOLOGY OF CULT FILMS: Reading Rocky Horror

This article provides a sociological reading of cult films, in particular, The Rocky Horror Picture Show. Cult films are secular documents, celebrated as sacred texts by audiences and used as shared foci to collectively create rituals and belief systems. They differ from popular re-releases, fad films, films with cult qualities, and critical cult films in that they involve typical people in atypical situations, sympathetic deviance, challenges to traditional authority, reflections of societal strains, and paradoxical and interpretable resolutions. Examination of the Rocky Horror text and the cult activities that occur during its viewing, reveal it as a paradoxical indictment and validation of traditional societal arrangements.     

Audience effects on solitary faces during imagery: Displaying to the people in your head

Subjects imagined situations in which they reported enjoying themselves either alone or with others. Electromyographic (EMG) activity was recorded bilaterally from regions overlying thezygomatic major muscles responsible for smiling. Controlling for equal rated happiness in the two conditions, subjects showed more smiling in high-sociality than low-sociality imagery. In confirming imaginary audience effects during imagery, these data corroborate hypotheses that solitary facial displays are mediated by the presence of imaginary interactants, and suggest caution in employing them as measures of felt emotion.Avery Gilbert and Amy Jaffey had compelling insights throughout the course of study. We thank Paul Ekman, Carroll Izard, and Paul Rozin for extensive comments on earlier drafts. We also thank Bernard Apfelbaum, Jon Baron, Janet Bavelas, John Cacioppo, Linda Camras, Dean Delis, Rob DeRubeis, Alan Fiske, Stephen Fowler, Greg McHugo, Harriet Oster, David Premack, W. John Smith, and David Williams for their valuable comments and suggestions.     

GM Foods and the Misperception of Risk Perception

Public opposition to genetically modified (GM) food and crops is widely interpreted as the result of the public's misperception of the risks. With scientific assessment pointing to no unique risks from GM crops and foods, a strategy of accurate risk communication from trusted sources has been advocated. This is based on the assumption that the benefits of GM crops and foods are self-evident. Informed by the interpretation of some qualitative interviews with lay people, we use data from the Eurobarometer survey on biotechnology to explore the hypothesis that it is not so much the perception of risks as the absence of benefits that is the basis of the widespread rejection of GM foods and crops by the European public. Some respondents perceive both risks and benefits, and may be trading off these attributes along the lines of a rational choice model. However, for others, one attribute-benefit-appears to dominate their judgments: the lexicographic heuristic. For these respondents, their perception of risk is of limited importance in the formation of attitudes toward GM food and crops. The implication is that the absence of perceived benefits from GM foods and crops calls into question the relevance of risk communication strategies for bringing about change in public opinion.     

MIMCA: multiple imputation for categorical variables with multiple correspondence analysis

We propose a multiple imputation method to deal with incomplete categorical data. This method imputes the missing entries using the principal component method dedicated to categorical data: multiple correspondence analysis (MCA). The uncertainty concerning the parameters of the imputation model is reflected using a non-parametric bootstrap. Multiple imputation using MCA (MIMCA) requires estimating a small number of parameters due to the dimensionality reduction property of MCA. It allows the user to impute a large range of data sets. In particular, a high number of categories per variable, a high number of variables or a small number of individuals are not an issue for MIMCA. Through a simulation study based on real data sets, the method is assessed and compared to the reference methods (multiple imputation using the loglinear model, multiple imputation by logistic regressions) as well to the latest works on the topic (multiple imputation by random forests or by the Dirichlet process mixture of products of multinomial distributions model). The proposed method provides a good point estimate of the parameters of the analysis model considered, such as the coefficients of a main effects logistic regression model, and a reliable estimate of the variability of the estimators. In addition, MIMCA has the great advantage that it is substantially less time consuming on data sets of high dimensions than the other multiple imputation methods.