Competent and Warm but Unemotional: The Influence of Occupational Stereotypes on the Attribution of Emotions

The present research aims to assess how occupational stereotypes, and in particular, stereotypes about doctors, influence the observers’ perception of the emotions expressed by members of this group. For this, 60 men and women judged the emotions of women who expressed either happiness, anger, sadness, or a neutral expression and whose faces were either uncovered or covered with a surgical mask, a niqab, or a hat and scarf such that only an identical portion of the face around the eyes was visible. Congruent with the occupational stereotype, women dressed as doctors were perceived highest on competence and warmth, but also as emotionally restrained such that they were rated as experiencing lower levels of emotions relative to the same women wearing other face covers or with uncovered faces.     

A note On outlier sensitivity of Sliced Inverse Regression

Sliced Inverse Regression (SIR) is a promising technique for the purpose of dimension reduction. Several properties of this method have been examined already, but little attention has been paid to robustness aspects. In this article, we focus on the sensitivity of SIR to outliers and show in what sense and how severely SIR can be influenced by outliers in the data.     

A note on contamination models and outliers

In order to describe or generate so-called outliers in univariate statistical data, contamination models are often used. These models assume that k out of n independent random variables are shifted or multiplicated by some constant, whereas the other observations still come i.i.d. from some common target distribution. Of course, these contaminants do not necessarily stick out as the extremes in the sample. Moreover, it is the amount and magnitude of ‘contamination” which determines the number of obvious outliers. Using the concept of Davies and Gather (1993) to formalize the outlier notion we quantify the amount of contamination needed to produce a prespecified expected number of ‘genuine’ outliers. In particular, we demonstrate that for sample of moderate size from a normal target distribution a rather large shift of the contaminants is necessary to yield a certain expected number of outliers. Such an insight is of interest when designing simulation studies where outliers shoulod occur as well as in theoretical investigations on outliers.     

Multivariate Real-Time Signal Extraction by a Robust Adaptive Regression Filter

We propose a new regression-based filter for extracting signals online from multivariate high frequency time series. It separates relevant signals of several variables from noise and (multivariate) outliers.

Unlike parallel univariate filters, the new procedure takes into account the local covariance structure between the single time series components. It is based on high-breakdown estimates, which makes it robust against (patches of) outliers in one or several of the components as well as against outliers with respect to the multivariate covariance structure. Moreover, the trade-off problem between bias and variance for the optimal choice of the window width is approached by choosing the size of the window adaptively, depending on the current data situation.

Furthermore, we present an advanced algorithm of our filtering procedure that includes the replacement of missing observations in real time. Thus, the new procedure can be applied in online-monitoring practice. Applications to physiological time series from intensive care show the practical effect of the proposed filtering technique.     

Estimating the density of a possibly missing response variable in nonlinear regression

This paper considers linear and nonlinear regression with a response variable that is allowed to be “missing at random”. The only structural assumptions on the distribution of the variables are that the errors have mean zero and are independent of the covariates. The independence assumption is important. It enables us to construct an estimator for the response density that uses all the observed data, in contrast to the usual local smoothing techniques, and which therefore permits a faster rate of convergence. The idea is to write the response density as a convolution integral which can be estimated by an empirical version, with a weighted residual-based kernel estimator plugged in for the error density. For an appropriate class of regression functions, and a suitably chosen bandwidth, this estimator is consistent and converges with the optimal parametric rate n^1/2. Moreover, the estimator is proved to be efficient (in the sense of Hájek and Le Cam) if an efficient estimator is used for the regression parameter.     

Habermas,Mead, and Rationality

This paper takes the position that symbolic interaction can become more relevant to the social issues of modernity and postmodernity by overcoming its traditional tendencies to be apolitical and to focus predominantly on micro aspects of social relations. It considers a serious reading of Habermas' Theory of Communicative Action as a contribution to this effort. Specifically it sees Habermas' reconstruction of the conception of the individual actor involved in communicating through significant symbols into one consistent with speech act theory and the concepts of speaker and listener as constructive and helpful. The paper also examines Mead's behav-ioristic theory of attitudes, types of attitudes and taking the attitude of the other(s), and relates it to his logical formulation of rational universals. It suggests that Mead's optimistic image of society and his position on rationality are no longer appropriate for discussing social issues in a global society with multiple rationalities. It sees possibilities for reformulation in Habermas' theory because, like Mead's theory, it construes rationality in communicative terms.     

New Media and Strategy Research: Towards a Relational Agency Approach

A rapidly growing body of literature focuses on the relationship between new media and strategy, and offers recommendations regarding appropriate strategic actions in relation to new media. This paper systematically reviews 130 articles with a focus on the diagnoses they provide and the directions they offer strategists regarding the role of new media in strategy. The analysis identifies four main ways of conceptualizing new media in the literature: as forces in an increasingly turbulent strategic environment; as changing the role of strategists; as tools for strategically engaging stakeholders; and as both increasing and decreasing the control necessary for strategy making. These conceptualizations are based on often‐implicit assumptions about ‘agency’ in strategy: new media are seen either as forces influencing strategy or as tools in the hands of humans, who are portrayed as the agents of strategy. In both cases, new media are black‐boxed, such that their specific properties and ways of becoming embedded in particular contexts are rarely examined. After discussing these assumptions and a limited number of studies that challenge them, the paper develops an approach to strategy and new media based on a relational understanding of agency, an attention to technological affordances and a methodological sensitivity to tracing strategy‐making assemblages of human and non‐human elements. We argue that future research based on this approach will advance our knowledge of strategy making in ways that do not take new media for granted and ways that are attentive to different kinds of agency.