More than Face Value: Context and Age Differences in Negative Emotion Discrimination

Journal of Nonverbal Behavior - Age-related deficits are often observed in emotion categorization tasks that include negative emotional expressions like anger, fear, and sadness. Stimulus...     

Can Children Recognize Bodily Expressions of Emotion?

Journal of Nonverbal Behavior - Past research has demonstrated that children understand distinct emotion concepts and can accurately recognize facial expressions of distinct emotions by a young...     

The Effect of Mergers and Acquisitions on Employees: Wealth Transfer,Gain‐Sharing or Pain‐Sharing?

This paper considers whether gains made by shareholders from corporate takeovers are achieved at the expense of employees, as proposed by the ‘wealth transfer’ perspective. It analyses the contribution of employee lay‐offs, along with employment and wage changes, to the takeover premium and abnormal share price movements. The analysis draws on a unique dataset of British takeovers, combining documentary, share price and accounting data. The results show that lay‐offs planned at the takeover have either no effect or adverse effects on shareholder returns. Wages growth is positively, not inversely, related to shareholder returns from the second year after the takeover, whilst positive employment changes have a similar effect in the following year. Closer scrutiny indicates that labour and shareholders share gains when the firm does well, but share pain when it does not. There is evidence, therefore, that labour and shareholder interests can be complementary, rather than antagonistic, after takeovers.     

A semi-parametric approach to robust parameter design

Parameter design or robust parameter design (RPD) is an engineering methodology intended as a cost-effective approach for improving the quality of products and processes. The goal of parameter design is to choose the levels of the control variables that optimize a defined quality characteristic. An essential component of RPD involves the assumption of well estimated models for the process mean and variance. Traditionally, the modeling of the mean and variance has been done parametrically. It is often the case, particularly when modeling the variance, that nonparametric techniques are more appropriate due to the nature of the curvature in the underlying function. Most response surface experiments involve sparse data. In sparse data situations with unusual curvature in the underlying function, nonparametric techniques often result in estimates with problematic variation whereas their parametric counterparts may result in estimates with problematic bias. We propose the use of semi-parametric modeling within the robust design setting, combining parametric and nonparametric functions to improve the quality of both mean and variance model estimation. The proposed method will be illustrated with an example and simulations.     

Activities of People with Moderate to Severe Learning Difficulties: living with purpose or just killing time?

In this study, intensive observational methods were used to examine the daily flow of activity of 12 people with moderate to severe learning difficulties living in long-stay hospital, and 12 people living in community based hostels. This covered the participants' full waking day and included weekend observations. The qualitative findings demonstrated how the participants played an active part in determining their own lifestyles. A number of more active hospital participants dealt with the unstimulating functional regime by attempting to create a social niche for themselves. A number of less active participants coped with the hospital environment by withdrawing into themselves and engaging in stereotypical behaviour to mark the passing of time. While the hostels provided a more homely and supportive environment, the participants tended to occupy a peripheral status as the least able people in the hostels and day centres. Consequently, they often had to seek staff support for activity or turned inwards. The quantitative findings followed a similar pattern of results to previous research in this area.     

ANOTHER LOOK AT THE STRATIFICATION OF EDUCATIONAL TRANSITIONS: THE LOGISTIC RESPONSE MODEL WITH PARTIAL PROPORTIONALITY CONSTRAINTS

In this paper we reanalyze Robert D. Mare's highly influential work on educational transitions among American men born in the first half of the 20th century. Contrary to previous belief, Mare found that the effects of socioeconomic background variables decline regularly across educational transitions in conditional logistic regression analyses. We have reconfirmed Mare's findings and tested them by introducing a modified logistic response model that constrains selected social background effects to vary proportionally across educational transitions. We refer to our preferred model as the logistic response model with partial proportionality constraints (LRPPC). The model can easily be estimated in Stata or using other standard statistical software. Partial proportionality constraints may also prove useful in interpopulation comparisons based on other linear models.