Sunday, November 17, 2019

Young adult siblings and twins are less alike in cognitive ability in highly educated families than in less educated families

Does sibling and twin similarity in cognitive ability differ by parents’ education? Tina Baier. ZfF – Journal of Family Research, 1-2019, pp. 58-82.

Abstract: Stratification scholars predominantly investigate how differences among children from different families emerge and tend to neglect differences among children from the same family. I study sibling similarity in cognitive ability and examine whether their similarity varies by parents’ education. Although economic approaches and their extensions argue that disadvantaged parents reinforce differences while advantaged parents compensate for differences, I argue that parents may also make equal investments and thus accept differences among their children. I refer to the literature on stratified parenting that demonstrates that parents are engaged differently in child-rearing and their children’s skill formation processes. Because advantaged parents foster children’s talents more individually compared with disadvantaged parents, I propose that sibling similarity is lower in advantaged than in disadvantaged families. Previous studies based on sibling correlations provide conflicting evidence. To account for observable and unobservable differences among siblings, I extend the established sibling correlation approach and study dizygotic and monozygotic twins in addition to siblings. The analyses draw on novel data from a population register-based study of twin families. I find that young adult siblings and twins are less alike in cognitive ability in highly educated families than in less educated families. Hence, my results support the hypothesis concerning equal investments and indicate that stratified parenting has a long-lasting influence on children’s cognitive ability.

Key words: intergenerational transmission; educational inequality; cognitive ability; sibling correlations; twins; Germany

5. Discussion and conclusion

I studied sibling similarity in cognitive ability and asked whether the degree of similarity
varies with parents’ education. In contrast to previous research, I extended the established
sibling correlation approach to DZ and MZ twins. This acknowledges the increasing evidence that genetic variation matters for cognitive ability and allows us to capture shared
family influences more comprehensively, and thus to test rigorously the link between sibling similarity and parents’ education.
To explain a varying degree of similarity, I first referred to economic approaches that
model parents’ investment decisions within the household (Becker/Tomes 1976; Behrman/Pollak/Taubman 1982). Against this backdrop, I tested the hypothesis that sibling
similarity in disadvantaged families is lower for efficiency reasons, whereas highly educated families compensate for, and thus equalize, differences among siblings (Conley
2004, 2008). I then introduced the idea that parents might also invest equally in and accept differences among their children. I drew on the literature on stratified parenting (e.g.,
Cheadle/Amato 2011; Kalil/Ryan/Corey 2012; Lareau 2011; Lareau/Weininger 2003) and
put it in a within-family perspective. Because advantaged parents adopt an active role in
shaping the developmental processes of their children and tend to provide more skillenhancing and specific inputs in line with children’s potentials and needs, I hypothesized
alternatively that siblings from advantaged families are less similar in terms of cognitive
ability compared with siblings from disadvantaged families. 
My analyses yielded two findings. First, young adult siblings, DZ twins, and MZ
twins in highly educated families are less alike in terms of cognitive ability compared
with young adult siblings, DZ twins, and MZ twins in less educated families. This contradicts the hypothesis concerning stratified investments rationales, according to which sibling similarity increases with parents’ social background (H1), and supports the hypothesis concerning equal investments and stratified parenting (H2).
Systematic differences in the degree of similarity in cognitive ability are significant in
the sibling sample. This is in line with US findings for literacy skills (Conley/Pfeiffer/
Velez 2007) but differs from the finding for Germany (Grätz 2018). One explanation of
the divergent findings could be that the families I studied have more children (twins and
at least one sibling) than the families in the study by Grätz (2018). Unfortunately, this
study does not provide information about the variance components in absolute terms. The
ICC is a standardized measure that does not change if the variances of shared family and
child-specific influences in absolute terms change at the same time. Thus, there might be
some variation in the relative importance of shared family influences that did not show up
in the ICC. To evaluate to what extent results differ substantially, we would also need information on the family level variation in absolute terms.
For both DZ twins and MZ twins, the results reveal the same pattern. The similarity
decreases according to parents’ education, though it is not statistically significant. Nonetheless, both the results for the variance components in absolute terms and for the ICC
confirm that shared family influences decrease the more educated parents are. Thus, the
more resources parents have, the more important are processes within the family that accentuate differences within the family.
In addition, I found that the mean level of cognitive ability increases with parents’ education, whereas the relative importance of shared family influences decreases. These divergent
trends show that the same shared family influences that make siblings and twins more alike
are also associated with lower levels of cognitive ability. This is a very important aspect, and
more research is needed to understand what kind of influences affect siblings equally and
hamper the realization of cognitive ability in less educated families. In advantaged families,
by contrast, parents often provide additional inputs that foster children’s talents. These influences are more child specific, which leads to higher levels of cognitive ability and promotes
differences in cognitive ability among their children. Given that differences between siblings
and twins from advantaged and disadvantaged backgrounds remain even as the children grow
older, my results indicate a long-lasting impact of parenting on cognitive ability.
Second, my results show that the association between parents’ educational background and sibling and twin similarity is not affected by the closeness of the sibling and
twin relationship. I thereby address a major limitation of studies on sibling similarity. In a
similar vein, my results reveal a very similar trend for siblings, DZ twins, and MZ twins,
which shows that there is no “twinning effect” – that is, that twins behave profoundly differently from (full) siblings.
However, it is important to note that I used an indicator that was measured at the
same time as cognitive ability. Since the quality of the sibling and twin relationship might
change over the life course, it is important to back up my results – ideally, with longitudinal data. To the extent that there are no profound changes in the sibling and twin relationship until early adulthood, my results are reliable. 
This study is the first to adopt a genetically sensitive approach to sibling similarity in
cognitive ability. The results provide strong indications for parent’s investment decisions
that are not in line with economic theories, rather parents invest equally in their children
but in distinct ways that differ according to parents’ educational background. My findings
challenge the implicit assumption that shared family influences such as parents’ education
influence children in similar fashion. Moreover, if children are raised in advantaged families, shared family influences – those that differ between families – are less important.
Genetically sensitive research can help us to better understand what kinds of parental investment – net of genetic influences – result in within-family stratification, and to formulate informative policy suggestions to enhance the achievements of children from less educated families.

Also: The Social Stratification of Environmental and Genetic Influences on Education: New Evidence Using a Register-Based Twin Sample. Tina Baier, Volker Lang. Sociological Science, February 20, 2019. 10.15195/v6.a6
The relative importance of genes and shared environmental influences on stratification outcomes has recently received much attention in the literature. We focus on education and the gene-environmental interplay. Specifically, we investigate whether—as proposed by the Scarr-Rowe hypothesis—genetic influences are more important in advantaged families. We argue that the social stratification of family environments affects children’s chances to actualize their genetic potential. We hypothesize that advantaged families provide more child-specific inputs, which enhance genetic expression, whereas the rearing environments of children in disadvantaged families are less adapted to children’s individual abilities, leading to a suppression of genetic potential. We test this relationship in Germany, which represents an interesting case due to its highly selective schooling system characterized by early tracking and the broad coverage of part-time schools. We use novel data from the TwinLife panel, a population-register–based sample of twins and their families. Results of ACE-variance decompositions support the Scarr-Rowe hypothesis: Shared environmental influences on education matter only in disadvantaged families, whereas genetic influences are more important in advantaged families. Our findings support the growing literature on the importance of the gene-environmental interplay and emphasize the role of the family environment as a trigger of differential genetic expression.

Unlike other forms of antisocial behavior, the findings do not reveal a relationship between two different heart rate measures and white-collar offending

Heart Rate Fails to Predict White Collar Crime. Nicole Leeper Piquero et al. American Journal of Criminal Justice, October 17 2019.

Abstract: This paper joins two strands of research: a focus on the influence of heart rate on antisocial behavior and the correlates of white-collar offending. With respect to the former, resting heart rate has been found to be one of the most replicable of all biological correlates of many different types of antisocial behavior and psychopathology. However, researchers studying the correlates of white-collar offending have only just begun to examine individual characteristics – and as of yet, have not examined the extent to which heart rate is a relevant correlate. Using data from a community sample of over a hundred males, this paper examines whether heart rate is associated with white-collar offending. Unlike other forms of antisocial behavior, the findings do not reveal a relationship between two different heart rate measures and white-collar offending. Directions for future research are noted.

Keywords: Heart rate White-collar offending Biosocial

The large sex differences in being arrested, pleading guilty, being sentenced, & being incarcerated are consistent with lifetime violent behavior, low self-control, IQ, parental socialization, & social support; that is, the differences seem justified

Self-Reported Male-Female Differences in Criminal Involvement Do Not Account for Criminal Justice Processing Differences. Kevin M. Beaver, John Paul Wright. American Journal of Criminal Justice, December 2019, Volume 44, Issue 6, pp 859–871.

Abstract: Disparities between males and females in criminal behavior have been widely documented. Despite the extensive amount of research examining sex differences in criminal and analogous behaviors, there is no consensus on whether self-reported misbehavior accounts for the large sex differences found in all phases of the criminal justice system. The current study explores whether, and to what degree, self-reported misconduct accounts for male-female differences. To do so, data drawn from the National Longitudinal Study of Adolescent to Adult Health (Add Health) were analyzed. Consistent with prior research, the results revealed statistically significant and substantively large male-female differences in being arrested, pleading guilty, being sentenced to probation, and being incarcerated. These disparities were unaffected by self-reports of lifetime violent behavior, lifetime non-violent behavior, low self-control, IQ, parental socialization, and social support.

Keywords: Add health Criminal justice Female Male Sex differences


A long line of research has revealed that males are disproportionately engaged in crime
and other acts of aggression and that they are processed through the criminal justice
system at much higher levels than females. Males are significantly more likely to be
arrested, incarcerated, and sentenced to lengthier prison terms than are females (Ellis
et al., 2009). The factors accounting for male-female differences, however, have been
somewhat elusive. The current study attempted to shed some light on the potential
factors that might explain male-female differences in being arrested, pleading guilty,
being sentenced to probation, and being incarcerated. Analysis of data drawn from the
Add Health revealed two key findings.
First, and in line with previous research (Ellis et al., 2009), the analyses revealed
robust male-female differences in the criminal justice processing variables. In comparison to the odds for females, the odds that males would be arrested was 3.74 times
greater, that they would plead guilty was 3.96 times greater, that they would be
sentenced to probation was 3.93 times greater, that they would be incarcerated was
3.91 times greater, and that they would be incarcerated if arrested was 1.45 times
greater. These differences were all statistically significant and quite large.
The second key finding to emerge from the analyses was that the male-female
disparities in criminal justice processing were largely immune to the effects of
covariates—including measures of some of the most consistent and robust predictors
of contact with the criminal justice system, such as involvement in violent and
nonviolent behavior, self-control, IQ, exposure to delinquent peers, and maternal as
well as paternal socialization variables. Although the male-female gap was slightly
attenuated in the multivariate models, the reductions were very small, ranging from 4 to
12%. This is a particularly noteworthy finding and highlights just how robust the male-
female differences were in the data.
While these analyses cannot provide definitive evidence of the processes that lead to
males being disproportionately processed through the criminal justice system, they do
tend to rule out some of the more common explanations. For instance, including
covariates for lifetime violent behavior and lifetime nonviolent behavior and having
the male-female gap remain strong and statistically significant tends to suggest that
male over-involvement in criminal activities is not the driving force behind why males
are disproportionately processed in the criminal justice system. At the same time,
criminogenic traits, such as low self-control and IQ, appear to have little to no
substantive impact on sex disparities in the criminal justice system and neither do
parental socialization measures or social support.
Our findings suggest that factors other than differential involvement create and
sustain sex disparities in justice system processing. Given findings in the extant
literature, it seems likely that legally relevant variables, such as the number of prior
arrests, the seriousness of the current crime, the presence of witnesses, and the desire of
victims to press charges, are the likely factors driving sex differences in processing.
Males, for example, account for the vast majority of homicides, rapes, and armed
robberies—crimes where system discretion is more limited and where penalties, such as
incarceration, are almost certain if convicted.
We would be remis not to contrast the literature on sex disparities in justice processing
with the literature on racial differences in processing. By any measure, sex disparities are
substantially larger and more indelible than are racial disparities. Indeed, in prior analyses
of these data, racial disparities in self-reported justice system processing were accounted
for using a limited number of measures (Beaver et al., 2013). And where several studies
find that legally relevant variables account for all, or almost all, of racial disparities in
processing, just the opposite is true of the literature on sex disparities in processing. Given
our findings, and those reported by others, it would appear that the criminal justice system
is sexist in its application of justice. However, we suggest that the system is rationally
sexist. Men are more physically violent than women, are physically more capable of
inflicting harm on others, and they engage in crimes where personal injury is more likely.
The criminal careers of men are also longer than women’s, they accelerate their offending
more quickly and have an earlier age of onset than women, and they take longer to desist
(Moffitt, 1993; Wright, Tibbetts, & Daigle, 2008). In turn, men represent a greater
comparative social threat to the safety of others and to the communities within which
they live. The large sex disparities found in the literature, and in our analysis of a national
sample, exist in part because they reflect the rational legal and institutional responses to
more fundamental differences between men and women in their use of physical
aggression. If true, women are more likely to be channeled out of the criminal justice
system for reasons not entirely associated with their participation in a criminal event. In
general, women are less physically dangerous than men and pose less a social threat than
men even if they engage in the same criminal event with a male.
The findings revealing significant male-female differences in criminal justice processing
should be viewed cautiously owing to a number of limitations. First, all of the criminal
justice processing variables were based on retrospective self-reported data which leaves
open the possibility of recall bias. It would be interesting and important to replicate these
analyses with data that included official crime measures. Unfortunately, the Add Health
data do not include such measures and so other samples will have to be employed in order
to address this shortcoming. Second, the data were based on a nationally representative data
which translates into relatively few chronic offenders. Again, an important avenue for
future research would be to analyze samples that have a substantially greater number of
violent offenders to determine whether these findings would remain robust to such
differences in the composition of the sample. Last, the Add Health data that are currently
available only followed respondents into their 30s. This necessarily leaves open the
possibility that the findings might change if the age range of respondents reached later
into adulthood. Future research would benefit by addressing these limitations and determining whether the findings presented here would be replicated in other samples.