Intangibles and the Gender Wage Gap: An Analysis of Gender Wage Gaps Across Occupations in the Finnish Private Sector

The paper compares the gender wage differentials of two occupation groups—innovation and non-innovation workers—separately for manufacturing and services using Finnish private-sector data. We apply a decomposition method based on unconditional quantile regression techniques to identify key factors underlying the gender wage gaps observed along the whole wage distribution, as well as changes in these wage gaps between 2002 and 2009. This more nuanced approach provides important new insights. We find conspicuous differences in average gender wage gaps, in gender wage-gap profiles across the wage distribution and also in the evolution of gender wage differentials over time between sectors and occupation groups. Our results imply that sector-specific factors are a more important driving force behind these differences in patterns and trends of gender wage gaps, although occupation-specific factors cannot be totally dismissed. Hence, comparisons of gender wage gaps, including their underlying sources, of innovation and non-innovation workers for too broadly defined segments of the labour market may result in misleading conclusions concerning the factual role of intangible capital.     

The mental health of the never-married

Although the interaction between mental health and marital status has been the object of much social scientific research, little is known about the mental health of never-married people. This article reviews research relevant to mental health and marital status as it pertains to never-marrieds. Methodological problems and current gaps in such research are pointed out. The mental health of never-marrieds is examined from three popular models of mental health—the social protection, social reaction, and social selection models. Each model offers competing explanations for differences in rates between married and unmarried people and between unmarried men and women. Suggestions are offered for improvement in researching the mental health of this neglected group.     

The time it takes to identify facial expressions: Effects of age,gender of subject,sex of sender,and type of expression

Subjects were presented with 35 mm slides of faces and required to indicate the type of expression (pleasant or unpleasant) by a switch movement. Latency and accuracy were recorded. The variables of the study were age (early or late adolescence), gender of subject, sex of sender, and type of expression. The most important results were as follows: There was no age effect when the latencies were adjusted by a covariate to take account of age-related differences in general perceptual-motor skills. There was a strong interaction in which the female pleasant slides produced substantially lower latencies than the other three combinations of sex of sender and type of expression. A weaker interaction indicated faster identification for the female sender, female subject condition than the other three combinations of sex of sender and gender of subject. Overall, the facial identification process was found to be very rapid (about a quarter of a second slower than identification of a simple geometric form) and accurate (.078 error rate).     

The Gambling Cognitions Inventory: scale development and psychometric validation with problem and pathological gamblers

Cognitive distortions are typically identified as an important etiological factor in pathological gambling. The Gambling Cognitions Inventory (GCI) developed by Holub (2003) is examined in this study using a sample of 710 pathological gamblers collected in four Canadian studies. Confirmatory factor analysis did not support the initial 40-item scale and suggested a 33-item scale. The sample was split into two groups to conduct exploratory and confirmatory factor analyses. Scree plots and parallel analysis suggested a two-factor scale. The scale developed by exploratory factor analysis on the first sample was supported by confirmatory factor analysis on the second sample (CFI>0.95; RMSEA < 0.05). The two factors indicated a Skill and Attitude subscale and a Luck and Chance subscale. Analysis conducted within each of the four studies showed good internal reliability for the scale (range of α = 0.91–0.95) and subscales (α = 0.77–0.92). The scale and subscales correlated with gambling severity measures as well as other measures of gambling cognitions including the Gambling Attitudes and Beliefs Scale and the Gambling Beliefs Questionnaire. The results of the study indicate that the GCI is a psychometrically strong scale and may be beneficial in directing cognitive therapy to the most problematic cognitions.     

Combination of Cancer Data in Quantitative Risk Assessments: Case Study Using Bromodichloromethane

There are often several data sets that may be used in developing a quantitative risk estimate for a carcinogen. These estimates are usually based, however, on the dose-response data for tumor incidences from a single sex/strain/species of animal. When appropriate, the use of more data should result in a higher level of confidence in the risk estimate. The decision to use more than one data set (e.g., representing different animal sexes, strains, species, or tumor sites) can be made following biological and statistical analyses of the compatibility of these data sets. Biological analysis involves consideration of factors such as the relevance of the animal models, study design and execution, dose selection and route of administration, the mechanism of action of the agent, its pharmacokinetics, any species- and/or sex-specific effects, and tumor site specificity. If the biological analysis does not prohibit combining data sets, statistical compatibility of the data sets is then investigated. A generalized likelihood ratio test is proposed for determining the compatibility of different data sets with respect to a common dose-response model, such as the linearized multistage model. The biological and statistical factors influencing the decision to combine data sets are described, followed by a case study of bromodichloromethane.