The Effect of Asymmetric Intersexual Selection Power Perception on the Choice Deferral Behavior of Men and Women

Consumers always delay their choices, which can cause companies to suffer tremendous losses. One reason for such delay is a lack of confidence. Confidence in consumer decision-making can stem from many sources, including social power. In this research, we find that selection power with regard to choosing a romantic mate increases consumers' decision confidence and, in turn, decreases choice deferral. We define the concept of intersexual selection power (ISP), and propose certain factors that can induce individuals' asymmetric ISP. We conducted four studies to explore four factors that could influence consumers' ISP perceptions (sex, mating cues, sex ratio, and mate value) and the effects of such power perception on choice deferral. The results showed that individuals with high ISP perception have more decision confidence and a lower choice deferral rate than individuals with low ISP perception regardless of the way in which choice deferral is measured.

Adolescent school injuries and classroom sex compositions in German secondary schools

BACKGROUND

School injuries are an important adolescent health problem. Previous research suggests that relevant risk behaviors for school injuries, risk-taking and aggression, are highly susceptible to peer effects. Specifically, evidence suggests that the ratio of men and women in peer groups (sex ratio) affects individuals' propensity for aggression and risk-taking. However, potential associations of classroom sex ratios with adolescent school injury risks have not been studied so far. The purpose of this paper is to investigate the association of classroom sex compositions with adolescent school injuries.

METHODS

We investigate the association of classroom sex ratios with school injuries in a longitudinal survey dataset containing 13,131 observations from 9,204 adolescent students (ages 13-16) from secondary schools in Germany. The data also allow us to identify injuries due to aggressive behavior and analyze these injuries in detail. We use multilevel logistic regression models to analyze risks of both overall and aggression-related school injuries.

RESULTS

Adolescent students' risk for school injuries is significantly and positively associated with male-skewed classroom sex ratios (OR = 1.012, p=0.012). Specifically, the risk of sustaining a school injury increases by 33.5 percent when moving from the 10th to the 90th classroom sex ratio percentile. Moreover, we find an even stronger positive association between male-dominated classrooms and aggression-related injury risks (OR = 1.022, p=0.010). Compared to classroom sex ratios at the 10th percentile, the risk of an aggression-related injury is 78 percent higher in classrooms with a sex ratio at the 90th percentile. Finally, we find that both boys' and girls' injury risks equally increase with a higher proportion of male students in their classroom.

CONCLUSIONS

Our findings indicate that sex composition of classrooms is an important contextual factor for adolescent school injuries, in particular school injuries resulting from aggression. These findings illustrate the need to integrate a contextual perspective on school injuries among adolescent students both into research and into intervention planning.

Convergent evidence for a theory of rapid, automatic, and accurate sex ratio tracking

It is presumed that people track the sex ratios in their environment (the number of males relative to number of females) in order to adaptively adjust their decisions and behaviors, but this actual tracking ability has not been established. The relevance of sex ratio information, drawn from evolutionary biology and studies of human relationship decision making, is integrated here with memory research (on frequency encoding), perception research (on ensemble coding), and neuroscience research. A series of four experiments provide empirical results to help fill research gaps and facilitate this theoretical integration. In particular, these studies connect details from memory research on relatively automatic frequency encoding of both items and categories, perception research on summary statistics from ensemble coding, and theoretical ideas about the function of these abilities (specifically applied to human sex ratios based on faces) from social and evolutionary approaches. Collectively this research demonstrates an evolved psychological mechanism for functional, fast, and relatively automatic human abilities to track experienced sex ratios in the social world. This sex ratio information is theorized to underpin documented facultative adjustments in relationship dynamics as well as perceptions of social group characteristics. This integrative approach highlights how the coding, memory, and judgments about population sex ratios can both account for a number of existing findings and point towards key further research.

Ecological Sex Ratios and Human Mating

The ratio of men to women in a given ecology can have profound influences on a range of interpersonal processes, from marriage and divorce rates to risk-taking and violent crime. Here, we organize such processes into two categories - intersexual choice and intrasexual competition - representing focal effects of imbalanced sex ratios.

Operational Sex Ratio Predicts Binge Drinking Across U.S. Counties

Previous research suggests that binge drinking among young men serves as a "costly signal" to potential mates, such that the binge drinker is capable of bearing the harmful consequences of alcohol consumption. Here, we propose that binge drinking among young adults is conditionally dependent upon the signaler's willingness to take risks, which is influenced by the local operational sex ratio (OSR). Using archived binge drinking estimates from 2009 to 2012 and Census Bureau records of OSRs, we tested the relationship between OSR and binge drinking rates at the county level across 3,143 U.S. counties against hypotheses drawn from evolutionary theory. Results from our mixed-effects models revealed that a higher overall OSR (i.e., more eligible men compared to women) was associated with higher male binge drinking rates but lower female binge drinking rates. A higher OSR particularly in the 20-29 and 50+ age groups predicted higher male binge drinking rates but lower female binge drinking rates. Our findings generally support predictions derived from evolutionary theory and suggest that binge drinking may function as a costly sexual signal, conditionally regulated by age and the local sex ratio.

The Perception of Operational Sex Ratios by Voice

Adult sex ratios in a local environment are linked to a wide variety of reproductive behaviors in humans and other animals. When sex ratios are biased, the more numerous sex faces increased competition for mates and is more likely to yield to the sociosexual preferences of the less numerous sex. Despite widespread evidence of the relationship between sex ratios and behavior, we know little about whether or how sex ratios are encoded and perceived. In two experiments men and women showed perceived sex ratios that correlated with actual sex ratios after 1500 ms exposures to groups of simultaneous voices. However, men perceived more female voices than women did, and women perceived more male voices than men did. Women showed better accuracy than men, but only when sex ratios departed markedly from 50%. Increasing the number of simultaneous voices reduced accuracy, but only at extreme sex ratios. Talker age also significantly affected perceived sex ratios, suggesting that perceived operational sex ratios are adaptively linked to the reproductive viability of the local population. The results suggest that listeners automatically encode vocal sex ratio information and that perceived sex ratios are influenced by characteristics of the local population and characteristics of the listener.

Sample-Size Planning for More Accurate Statistical Power: A Method Adjusting Sample Effect Sizes for Publication Bias and Uncertainty

The sample size necessary to obtain a desired level of statistical power depends in part on the population value of the effect size, which is, by definition, unknown. A common approach to sample-size planning uses the sample effect size from a prior study as an estimate of the population value of the effect to be detected in the future study. Although this strategy is intuitively appealing, effect-size estimates, taken at face value, are typically not accurate estimates of the population effect size because of publication bias and uncertainty. We show that the use of this approach often results in underpowered studies, sometimes to an alarming degree. We present an alternative approach that adjusts sample effect sizes for bias and uncertainty, and we demonstrate its effectiveness for several experimental designs. Furthermore, we discuss an open-source R package, BUCSS, and user-friendly Web applications that we have made available to researchers so that they can easily implement our suggested methods.