More confirmation of the Trivers-Willard hypothesis: Sons from high-status families achieve higher educational outcomes than daughters, while daughters from low-status families surpass sons

Parental background and daughters’ and sons’ educational outcomes – application of the Trivers-Willard hypothesis. Janne Salminen, Hannu Lehti. Journal of Biosocial Science, January 6 2023. https://www.cambridge.org/core/journals/journal-of-biosocial-science/article/parental-background-and-daughters-and-sons-educational-outcomes-application-of-the-triverswillard-hypothesis/47FD4388B618EB5E078336813FEB71E3

Abstract: This study uses Trivers-Willard hypothesis to explain the differences in daughters’ and sons’ educational outcomes by parental background. According to the Trivers-Willard hypothesis (TWH), parental support and investments for sons and daughters display an asymmetrical relationship according to parental status because of the different reproductive advantage of the sexes. It predicts that high-status parents support sons more than daughters, and low-status parents support daughters more than sons. In modern societies, where education is the most important mediator of status, the TW hypothesis predicts that sons from high-status families will achieve higher educational outcomes than daughters. Using cohorts born between 1987 and 1997 from the reliable full population Finnish register data that contain the data of over 600.000 individuals, children’s educational outcomes were measured using data on school dropout rate, academic grade point average (GPA), and general secondary enrollment in their adolescence. OLS and sibling fixed-effect regression that permitted an examination of opposite-sex siblings’ educational outcomes within the same family were applied. Sons with high family income and parental education, compared to daughters of the same family, have lower probability of dropping out of school and are more likely to enroll into academic secondary school track. In families with low parental education or income daughters have lower probability for school dropout and enroll more likely to academic school track related to sons of the same family. The effect of family background by sex can be interpreted to support TWH in dropout and academic school track enrollment but not in GPA.

Discussion

This study investigated whether parental socioeconomic resources influence sons and daughters differently. The biosocial theory – the Trivers-Willard hypothesis – which states that parents with high social status invest more in sons compared to low-status parents who invest more in daughters, was applied. Sibling fixed-effects regression models were utilised by observing how parental education and family income influence sons’ and daughters’ GPA, dropout rates from secondary school and general secondary enrollment with reliable Finnish register data.

The results show that parental education has a stronger positive effect on sons’ educational outcomes than daughters in all three measured outcomes. Family income has an even more pronounced effect for dropping out from secondary education and for general secondary enrollment. However, family income did not influence the GPA based on the siblings’ sex. These results are in line with previous studies that have studied TWH in the United States (Hopcroft, Reference Hopcroft2005; Hopcroft & Martin, Reference Hopcroft and Martin2016; Pink, Schaman, & Fieder, Reference Pink, Schaman and Fieder2017). Additionally, the results support the claim that boys are more sensitive to family’s resources than girls in terms of educational outcomes (Autor et al. Reference Autor, Figlio, Karbownik, Roth and Wasserman2019; Brenøe & Lunberg, Reference Brenøe and Lundberg2018).

The result that found the largest Trivers-Willard effect for general secondary enrollment compared to dropout and GPA indicates that parents may guide children’s educational decision-making process. Thus, parents probably give guidance to their children according to their own human and economic capital; however, this study adds that the guidance can be different for sons and daughters depending on family conditions. The biosocial mechanism explains why family conditions influence differently for sons’ and daughters’ education.

Limitations

Although we can obtain reliable information with register data, there are still some limitations despite large dataset and objective information. We were not able to obtain information about the exact nature of parental behavior for children’s benefit. The lack of direct measure of parental investment is the one limitation and thus it is difficult to observe exact mechanism between parental resources and child’s educational outcome.

However, previous studies show that parental SES and the amount of investment correlates highly (see Tanskanen & Danielsbacka, Reference Tanskanen and Danielsbacka2019). Further, the results show that parental education and family income had the strongest TWH effect on general secondary enrollment compared to dropout and GPA. Thus, it can be stated that the results of the study reflect parental investments in the form of human capital accumulation of the children, because children continue to pursue higher education very likely after general secondary education that leads to higher income and socioeconomic status in adulthood. However, parents may have lower possibilities to influence children’s risks of school dropout. Avoiding school dropout does not necessarily lead to high status in adulthood, but children who avoid dropout and continue secondary schooling avoid low status and income in adulthood. GPA is determined highly by children’s intelligence and other non-cognitive traits that parents find very difficult to influence in Finland due to the absence of private schools. It has been shown, for example, that individuals’ variations in GPA are largely explained by genes but not shared environmental effects such as family background (Nielsen, Reference Nielsen2006). Finnish schools that have very low variance and thus show low inequality of learning outcomes can even amplify the genetic effects and reduce the effects of parents and thus that of TWH on GPA.

This study could not control for health and psychiatric variables. Thus, the results may reflect the fact that boys have more learning difficulties than girls (for example in the case of ADHD and other neurotypical disabilities), particularly among low status families; however, the study controlled for GPA that considers at least some of the effect of learning disabilities.

The findings come from a Finnish birth cohort born in 1987–1997. This cohort has experienced relatively high equality of opportunity in school context and the egalitarian welfare state has supported their families throughout their childhood. For these cohorts, all education levels have been free of charge. The funding of the schools and universities are based on governmental finance. There is no private school at any education level. According to the Global Gender Gap Report (2021), Finnish society is the second most gender-egalitarian country in the world and on average, women are better educated than men. However, previous studies have shown that parental education rather than family income is associated with education and later social status in Nordic countries (Elstad & Bakken, Reference Elstad and Bakken2015; Erola et al., Reference Erola, Jalonen and Lehti2016) Surprisingly, the study still found that higher family income decreases the educational disadvantage for boys. Because this effect was found in the Nordic welfare context it suggests that in other countries with different institutional context that includes tuition fees, the effect of the family income could be even stronger. If TWH is seen as universal it should be influential despite the institutional context. The results support this interpretation because the effect is found also in contexts where parental resources should not matter for children’s education. This indicates that parents’ and children’s evolutionary adaptations that mold their cognitive architecture (biases) and behavior are effective in modern societies. Additionally, the result of family income is surprising because in contemporary western societies experience an abundance of resources that leads to high investment in all children (Hopcroft, Reference Hopcroft2005). It can be argued that the logic of the TWH is problematic because high status males do not have a higher probability to reproduce than high status females on an average in all modern societies due to the use of contraception (Hopcroft, Reference Hopcroft2005). However, this argument has not gained empirical support because previous studies show that still in many modern societies high status men have higher probability to have more children than lower status men (Nisén et al. Reference Nisén, Martikainen, Myrskylä and Silventoinen2018; Nettle & Pollet Reference Nettle and Pollet2008; Weeden et. al. Reference Weeden, Abrams, Green and Sabini2006; Lappegård & Rønsen Reference Lappegård and Rønsen2013; Hopcroft Reference Hopcroft2019). Furthermore, it is important to acknowledge while applying evolutionary explanations that individuals usually do not consciously try to increase their (inclusive) fitness and maximize the number of offspring as standard rational theories used in social science would assume. Instead, it is assumed that humans have cognitive mechanisms that guide them to put effort into things that would have tended to increase (inclusive) fitness during evolutionary history (Hrdy, Reference Hrdy2011). In an evolutionary framework, parental investments are defined as any investment by the parent in a child that increases the child’s likelihood to survive and hence reproductive success at the cost of the parent’s ability to invest in another child (Trivers, Reference Trivers

1972). Thus, parental investments mean parental behavior, for example parental care, that increases a child’s inclusive fitness. Therefore, future research should analyze parental behavior by combining register and survey data to get an even more thorough picture of TWH. 

No consistent associations of well-being & brain correlates

A systematic review of the neural correlates of well-being reveals no consistent associations. Lianne P.de Vries, Margot P. van de Weijer, Meike Bartels. Neuroscience & Biobehavioral Reviews, January 5 2023, 105036. https://doi.org/10.1016/j.neubiorev.2023.105036

Highlights

• We performed a systematic review on the neural correlates of well-being.

• A wide range of brain regions was involved in well-being in the different studies.

• More left than right brain activation might be related to higher well-being.

• Replication of associations across studies was scarce, in strength and direction.

• Well-powered brain-wide association studies are needed to study neural correlates of well-being.

Abstract: Findings from behavioral and genetic studies indicate a potential role for the involvement of brain structures and brain functioning in well-being. We performed a systematic review on the association between brain structures or brain functioning and well-being, including 56 studies. The 11 electroencephalography (EEG) studies suggest a larger alpha asymmetry (more left than right brain activation) to be related to higher well-being. The 18 Magnetic Resonance Imaging (MRI) studies, 26 resting-state functional MRI studies and two functional near-infrared spectroscopy (fNIRS) studies identified a wide range of brain regions involved in well-being, but replication across studies was scarce, both in direction and strength of the associations. The inconsistency could result from small sample sizes of most studies and a possible wide-spread network of brain regions with small effects involved in well-being. Future directions include well-powered brain-wide association studies and innovative methods to more reliably measure brain activity in daily life.

Keywords: well-beingbrainneural correlatesbrain-wide associations

Discussion

To understand observed differences in well-being between people in more detail, it is essential to identify the biological and neural factors related to well-being. The goal of this systematic review was to bring together the available literature on well-being and brain structures and brain functioning. We first summarize and discuss the findings and based on the results, we propose directions for future research.

Brain structure

The systematic review of the brain areas where grey matter volume was associated with well-being revealed large inconsistencies. While the grey matter volumes of the (medial) PFC, ACC, the precuneus, hippocampus, and brainstem were related to well-being in multiple studies, for all these areas, there was inconsistency in the direction of the associations. Whereas in some studies smaller grey matter volume of the PFC, ACC, precuneus, hippocampus, or brainstem was related to higher levels of well-being, in other studies a larger grey matter volume of these areas was related to higher well-being.

These discrepancies might be the result of the small sample sizes (ranging from 15 to 724) in most structural MRI studies. Especially if the effect sizes are small, a large sample size is needed to have enough power to detect associations (Marek et al., 2022). Only two studies included more than 700 participants and only five studies more than 200 participants, indicating the need for larger sample sizes before we are able to reliably test for an association between the structure and volume of brain areas and well-being.

More recent studies went beyond brain volume and reported for example that well-being was associated with higher orientation dispersion, i.e., brain development and more dendritic complexity (Cabeen et al., 2021). This suggests that other, more detailed, features of brain structures might be related to well-being. The development and application of higher resolution imaging sequences allows us to, for example, investigate the cortical microstructure and complexity of brain structures in relation to phenotypes in more detail (Zhang et al., 2012).

Brain functioning

EEG

Three studies related well-being to the profiles of resting EEG power. Resting EEG power measures spontaneous brain activity, which can be divided into different frequencies. In single studies, the slower frequency signals, theta and alpha, were negatively related to well-being, whereas delta power, a faster brain oscillation, was positively related to well-being. A recent and larger study reported only a relation between the interaction between alpha, beta, and delta power and well-being, whereas the relation between the power of the single frequency bands and well-being was not significant. This could indicate that the relative amplitude of different frequency bands is important for well-being instead of the absolute power of single frequency bands. However, replication in studies with larger sample sizes is needed to draw a conclusion on the association between well-being and the different frequency bands in the brain.

(Frontal) alpha asymmetry was examined in more studies and positively associated with a measure of well-being in seven of the nine studies, whereas the other studies did not report a significant effect. Additionally, the small meta-analysis of alpha asymmetry and well-being indicated a positive relation (r=.19), but also suggested a possible publication bias. If replicated, greater left than right frontal activation is associated with well-being. This is in line with theory that alpha asymmetry is related to approach motivation and therefore the experience of positive feelings (Angus and Harmon-Jones, 2016). The opposite asymmetry, greater right-frontal activity, is assumed to be involved in withdrawal motivation, and some studies have found a relation with depression (but see (Olbrich and Arns, 2013) for a discussion about the unsuccessful replications). Noteworthy is that most studies on alpha asymmetry included measures of positive affect and/or life satisfaction, whereas the psychological well-being scale was only included in one study. More research on the moderating effect of the well-being scale used is therefore needed in future studies.

fMRI/fNIRS

The results of the included studies on the associations of well-being and brain activity and functional connectivity across brain regions/networks are very heterogenous. As can be seen in Fig. 4, many brain regions across the whole brain were associated with well-being in the different studies. However, replication of the associations across multiple studies was mostly absent. Furthermore, if a brain region was associated with well-being in multiple studies, the direction of the association was inconsistent. For example, in the fMRI studies that associated the activity or functional connectivity of the PFC, orbitofrontal cortex or precuneus to well-being (respectively 14, 5 and 4 studies in total, see Supplementary Table S1), for all brain areas half of the associations with well-being were negative, whereas the other half were positive. The most consistent finding in fMRI studies that investigated the connectivity between brain areas in relation to well-being is that a stronger functional connectivity within the default mode network (DMN) is related to lower well-being. The DMN consists of brain regions in the ventral and dorsal medial PFC, and the PCC. This network of cooperating brain regions is active when a person is in resting state or when not focused on the outside world (Raichle, 2015). The DMN has been involved in daydreaming and mind wandering. The positive correlation between connectivity in the DMN and well-being suggests that the activity of several brain areas related to thinking spontaneously is connected stronger in happier people.

Interpretation

The results of the reviewed studies on the neural correlates of well-being are very heterogeneous. Across all studies and methods, brain areas most often associated with well-being were the PFC, ACC, insula, default mode network, orbitofrontal cortex, visual networks, precuneus, and somatosensory networks (see supplementary Table S1). The association between well-being and the structure and/or functioning of the PFC, ACC, insula, and precuneus was reported in studies using different techniques (e.g., fMRI, MRI and EEG). However, the direction and strength of these associations differed to a great extent and many other brain areas have been identified in single studies, but not replicated in other studies. We replicated part of the conclusions of (Machado and Cantilino, 2016) and (King, 2019) about the relations between well-being and various brain areas. However, the involvement of networks, like the DMN, visual, and somatosensory networks emerged mostly in more recent studies included in the current review.

A first explanation of the inconsistent results is the large differences in brain imaging methods and analysis techniques. Different brain functioning imaging methods might lead to different results, e.g., EEG and fMRI both assess brain functioning, but are completely different techniques with different temporal and spatial characteristics. The brain areas covered with these techniques are at the surface with EEG assessment, but include the whole brain with fMRI assessments. Furthermore, when using the same imaging technique, the analysis techniques differed a lot. For example, the resting state fMRI studies either applied fALFF, functional connectivity analyses, or regional homogeneity (ReHo) to assess the regional neural activity or connectivity between brain areas. Lastly, although it has been shown that the function of a brain area and its structure are related (Sui et al., 2014, Toosy et al., 2004), the findings of MRI and fMRI are not completely comparable. These differences in methods and analyses add a first difficulty in comparing the results of the studies and harmonization is needed in future studies.

In addition, a limitation in the field of imaging is the small sample sizes, mainly due to the costs, leading to low power of the study and low reproducibility of results (Button et al., 2013). As discussed in more detail in the section below, the small samples in combination with potential small effects of the involvement of single brain regions in well-being can explain the failure to replicate findings.

Brain-wide association studies

Similar to the inconsistent results of our review, meta-analyses and reviews on the association of brain regions with other behaviors or complex traits reported largely inconsistent results and a wide range of potentially associated brain regions as well. For example, in a meta-analysis of resting state fMRI studies of attention deficit hyperactivity disorder (ADHD), (Cortese et al., 2021) did not find any convergence of connectivity patterns across studies. The same replication problem was shown in a meta-analysis of brain regions in relation to depression ((Müller et al., 2017). Across 99 neuroimaging experiments there were large inconsistencies in results.

In light of these wide-spread replication problems across behaviors and traits, and related to the small sample sizes used in neuroimaging research, an explanation for the diversity in results could be the small effects of the involvement of single brain regions in well-being and other human behaviors and traits. Similar to findings of genome-wide association studies (GWAS) that indicate that there are no “well-being genes” with a large effect on well-being, but many genes with small effects (Baselmans et al., 2019a, Okbay et al., 2016), it is unlikely that there is a “well-being brain region” or a few brain areas that have large effects on well-being. In contrast, a wide network of brain areas that all have small effects on well-being is to be expected. Using GWAS as example, brain-wide association studies (BWAS) have been proposed to reliably and without a priori hypotheses investigate the involvement of the brain in human behavior and traits (Gong et al., 2018, Marek et al., 2022). BWAS with sufficiently large sample sizes, i.e., samples with thousands of individuals, are needed improve reproducibility and the reliability of the brain–behavioral phenotype associations. Following the example of the genetic community, neuroimaging research should start large-scale collaborations to create the needed large sample sizes that are mostly missing in brain-wide association analyses (Poldrack et al., 2017).

An example of an already worldwide collaborative network is the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium, including 100k+ participants and 45 countries that focuses on disorders (Thompson et al., 2014). For Major Depressive Disorder (MDD), this consortium has already led to reproducible results, including a smaller hippocampal volume in MDD participants (n= 1728) compared with healthy controls (n=7199) and lower cortical thickness in the cingulate cortex, bilateral medial OFC and insula (Schmaal et al., 2020). Similarly, for other disorders like ADHD, bipolar disorder, and schizophrenia, robust brain correlates have been found in the large ENIGMA samples. In a recent application of BWAS to cognitive ability and psychopathology with more than 10 thousand participants, (Marek et al., 2022) showed a widely distributed circuitry of associations. These patterns indicate the involvement of many brain areas not detected in studies with the typical smaller sample sizes. This approach of well-powered brain-wide association studies is needed to investigate the brain-well-being associations as well.

Furthermore, following the successful polygenic scores in the field of genetics (Wray et al., 2007), recently, the use of polyneuro scores has been proposed (Mooney et al., 2021). Polyneuro scores are summary scores of the cumulative effect of brain-wide measures that capture effects across widely distributed brain systems and regions that are involved in different human traits (Mooney et al., 2021). Applied to ADHD, (Mooney et al., 2021) showed that such summary scores of functional connectivity across the brain have increased predictive power for ADHD symptoms. The scores explained around 8 times more variation than the variation explained by the most significant connection in the brain. However, the explained variance is still small, ~4% of the variation in symptoms is explained by the polyneuro scores.

Returning to the results of our review on well-being, this idea of brain wide associations for well-being is supported by the wide range of brain areas potentially associated with well-being. Furthermore, some specific findings of the more recent studies are in line with brain wide associations. For example, the association of neural diversity or variability in functional connectivity and higher well-being suggests that a higher complexity or more connectivity, i.e., more collaboration between brain areas leads to higher well-being (Cabeen et al., 2021). However, future brain-wide association studies are needed to support this idea for well-being and to be able to create polyneuro scores for well-being. To create the large sample sizes that are needed for brain-wide association studies, existing brain consortia could either include a well-being questionnaire, or brain and well-being researcher could combine their efforts in large consortia.

Innovative methods and analyses

The rapid development in the methods and techniques that measure brain structure and functioning at smaller temporal and spatial resolution give rise to new opportunities as well. For example, recent studies on the microstructure of the brain enables investigations of the relation between well-being and more detailed aspects of brain structures and functioning (Cabeen et al., 2021). However, also with such research to microstructures, a brain-wide approach should be applied to prevent non-replicable results.

Another direction for future research is the improvement of ecological validity in neuroscience research. At the moment, most brain imaging research is conducted in MRI scanners or in a controlled setting in the lab. This raises the question of the ecological validity, i.e., the generalizability to daily life or to which extent the results predict behaviour outside the testing environment (Matusz et al., 2019). Various solutions have been thought of to enhance the ecological validity in neuroscience. As an example of using more naturalistic stimuli and tasks, (Reggente et al., 2018) reviewed the use of virtual reality in fMRI research to memory. The results suggest the neural correlates associated with virtual reality (VR) images are more likely to generalize to real-world behaviors. This might help to find the relevant neural correlates for daily life, without introducing more variation because of uncontrollable external influences that exist in daily life. Another way to enhance ecological validity is by using portable devices, such as portable EEG and fNIRS caps, to measure neural correlates in real life and daily life (Balardin et al., 2017). Recently a portable MEG helmet has been developed as well (Boto et al., 2018). These mobile methods lead to many more possibilities to measure and understand brain activity and functioning in real-life settings and scenarios. EEG has already been recorded during walking, cycling, sports, and even skateboarding (Ladouce et al., 2019, Park et al., 2015, Robles et al., 2021, Scanlon et al., 2019). Furthermore, people from all ages, including babies and children can participate more easily, as movement is less of an issue with the portable devices.

Related to innovations in the methods for neuroimaging, there are also rapid developments in the approaches to analyse (big) data. Using the developments in the artificial intelligence and machine learning fields, patterns can be detected in imaging data that we would not predict or expect. These approaches enable us to focus more on data-driven research instead of hypothesis driven research (Scheel et al., 2020). Using a data driving approach, (Liu et al., 2020) analysed fMRI data from major depressive patients and healthy controls. Their models could distinguish between the patients and healthy controls (accuracy=0.77) and the authors reported several brain-wide features that differed between patients and controls.

Limitations

Because of the inconsistency in study design, measures, neuroimaging analyses, and reported results, a meta-analysis on the association of brain areas and well-being was mostly not possible. Conclusions should therefore be drawn with caution. Although more studies are being performed currently, future research should be harmonised to allow meta-analyses and to reach the desired sample size of thousands of participants. Whereas we did perform a small meta-analysis on the association between frontal asymmetry and well-being, the estimate was based on only a few studies and the analysis pointed towards a potential publication bias. Therefore, these results should be interpreted with caution as well.

Furthermore, it is difficult to compare earlier neuroimaging studies to the more recent studies, because of the rapid technological advancements and changing guidelines and methods in the neuroscience field. In earlier research, regions of interest (ROIs) were decided up front, whereas nowadays a voxel-wise whole brain analysis is preferred. However, as mentioned before, most brain-wide studies did not include sufficiently large sample sizes. The often small sample sizes in neuroscience research are a limitation for interpreting the results reliably, since this increases the variability and reduces statistical power. As proposed, future studies should perform power calculations before running imaging studies and start collaborations to reach the required sample sizes for brain-wide association studies (Marek et al., 2022, Szucs and Ioannidis, 2020).

Papers and patents are becoming less disruptive over time

Papers and patents are becoming less disruptive over time. Michael Park, Erin Leahey & Russell J. Funk. Nature volume 613, pages138–144, Jan 4 2023. https://www.nature.com/articles/s41586-022-05543-x

Abstract: Theories of scientific and technological change view discovery and invention as endogenous processes1,2, wherein previous accumulated knowledge enables future progress by allowing researchers to, in Newton’s words, ‘stand on the shoulders of giants’3,4,5,6,7. Recent decades have witnessed exponential growth in the volume of new scientific and technological knowledge, thereby creating conditions that should be ripe for major advances8,9. Yet contrary to this view, studies suggest that progress is slowing in several major fields10,11. Here, we analyse these claims at scale across six decades, using data on 45 million papers and 3.9 million patents from six large-scale datasets, together with a new quantitative metric—the CD index12—that characterizes how papers and patents change networks of citations in science and technology. We find that papers and patents are increasingly less likely to break with the past in ways that push science and technology in new directions. This pattern holds universally across fields and is robust across multiple different citation- and text-based metrics1,13,14,15,16,17. Subsequently, we link this decline in disruptiveness to a narrowing in the use of previous knowledge, allowing us to reconcile the patterns we observe with the ‘shoulders of giants’ view. We find that the observed declines are unlikely to be driven by changes in the quality of published science, citation practices or field-specific factors. Overall, our results suggest that slowing rates of disruption may reflect a fundamental shift in the nature of science and technology.

Discussion

In summary, we report a marked decline in disruptive science and technology over time. Our analyses show that this trend is unlikely to be driven by changes in citation practices or the quality of published work. Rather, the decline represents a substantive shift in science and technology, one that reinforces concerns about slowing innovative activity. We attribute this trend in part to scientists’ and inventors’ reliance on a narrower set of existing knowledge. Even though philosophers of science may be correct that the growth of knowledge is an endogenous process—wherein accumulated understanding promotes future discovery and invention—engagement with a broad range of extant knowledge is necessary for that process to play out, a requirement that appears more difficult with time. Relying on narrower slices of knowledge benefits individual careers53, but not scientific progress more generally.

Moreover, even though the prevalence of disruptive works has declined, we find that the sheer number has remained stable. On the one hand, this result may suggest that there is a fixed ‘carrying capacity’ for highly disruptive science and technology, in which case, policy interventions aimed at increasing such work may prove challenging. On the other hand, our observation of considerable churn in the underlying fields responsible for producing disruptive science and technology suggests the potential importance of factors such as the shifting interests of funders and scientists and the ‘ripeness’ of scientific and technologicalknowledge for breakthroughs, in which case the production of disruptive work may be responsive to policy levers. In either case, the stability we observe in the sheer number of disruptive papers and patents suggests that science and technology do not appear to have reached the end of the ‘endless frontier’. Room remains for the regular rerouting that disruptive works contribute to scientific and technological progress.

Our study is not without limitations. Notably, even though research to date supports the validity of the CD index12,34, it is a relatively new indicator of innovative activity and will benefit from future work on its behaviour and properties, especially across data sources and contexts. Studies that systematically examine the effect of different citation practices54,55, which vary across fields, would be particularly informative.

Overall, our results deepen understanding of the evolution of knowledge and may guide career planning and science policy. To promote disruptive science and technology, scholars may be encouraged to read widely and given time to keep up with the rapidly expanding knowledge frontier. Universities may forgo the focus on quantity, and more strongly reward research quality56, and perhaps more fully subsidize year-long sabbaticals. Federal agencies may invest in the riskier and longer-term individual awards that support careers and not simply specific projects57, giving scholars the gift of time needed to step outside the fray, inoculate themselves from the publish or perish culture, and produce truly consequential work. Understanding the decline in disruptive science and technology more fully permits a much-needed rethinking of strategies for organizing the production of science and technology in the future.

We provide a novel finding that self-perceived attractiveness has significant (negative) effects on mask-wearing intention

Post COVID-19, still wear a face mask? Self-perceived facial attractiveness reduces mask-wearing intention. Seung Eun Cha, Xyle Ku and  Incheol Choi. Front. Psychol., Jan 4 2023. https://www.frontiersin.org/articles/10.3389/fpsyg.2023.1084941/abstract

Abstract: With the emerging post-COVID era, wearing face masks has become a domain of personal choice. Then, who wants to continue wearing a mask when it is no longer mandatory? In this article, we expect and examine the role of self-perceived attractiveness in predicting mask-wearing intention and its mechanism across three studies (total N = 1,030). Studies 1 and 2 demonstrated that individuals with high (vs. low) self-perceived attractiveness were less willing to wear a mask, due to a weaker endorsement of the belief that mask-wearing enhances their perceived attractiveness (i.e., mask attractiveness belief). Study 3 further revealed that this mediational association was stronger in situations where the need to deliver a favorable impression was high (job interview context) versus low (walking a dog context). Overall, we provide a novel finding that self-perceived attractiveness has significant effects on mask-wearing intention via mask attractiveness belief in the post-pandemic of COVID-19. Our findings suggest that mask-wearing can shift from being a self-protection measure during the COVID-19 pandemic to a self-presentation tactic in the post-pandemic era.

Evidence from Airports on the Effects of Infrastructure Privatization: We show that outright ownership rather than control rights alone is associated with the most improvement after privatization

All Clear for Takeoff: Evidence from Airports on the Effects of Infrastructure Privatization. Sabrina T. Howell, Yeejin Jang, Hyeik Kim & Michael S. Weisbach. NBER Working Paper 30544. Oct 2022. DOI 10.3386/w30544

Abstract: Infrastructure assets have undergone substantial privatization in recent decades. How do different types of owners target and manage these assets? And does the contract form—control rights (concession) vs. outright ownership (sale)—matter? We explore these questions in the context of global airports, which like other infrastructure assets have been privatized by private firms and private equity (PE) funds. Our central finding is that PE acquisitions bring marked improvements in airport performance along a rich array of dimensions such as passengers per flight, total passengers, number of routes, number of airlines, cancellations, and awards. Net income increases after PE acquisitions, which does not reflect lower costs or layoffs. In contrast, in the few cases where non-PE acquisitions bring some improvement, it appears to reflect targeting rather than operational changes. Overall, we find little evidence that privatization alone increases airport performance; instead, infrastructure funds improve performance both in privatization and subsequent acquisitions from non-PE private firms. These effects are largest when there is a competing airport nearby. Finally, we show that outright ownership rather than control rights alone is associated with the most improvement after privatization.

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A key metric of airport efficiency is passengers per flight. The more customers an airport can serve with existing runways and gates, the more services it can deliver and the more earnings it can generate. When PE funds buy government-owned airports, the number of passengers per flight rises an average 20 percent. There's no such increase when non-PE private firms acquire an airport. Overall passenger traffic rises under both types of private ownership, but the rise at PE-owned airports, 84 percent, is four times greater than that at non-PE-owned private airports. Freight volumes and the number of flights, other measures of efficiency, show a similar pattern. Evidence from satellite image data indicates that PE owners increase terminal size and the number of gates. This capacity expansion helps enable the volume increases and points to the airport having been financially constrained under previous ownership.

PE firms tend to attract new low-cost carriers to their airports, which in turn may lead to greater competition and offer consumers better service and lower prices. With regard to routes, PE acquirers increase the number of new routes, especially international routes, more than other buyers. International passengers are often the most profitable airport users, especially in developing countries.

A PE acquisition is also associated with a decline in flight cancellations and an increase in the likelihood of receiving a quality award. When an airport shifts from non-PE private to PE ownership, its odds of winning an award rise by 6 percentage points. The average chance of winning such an award is just 2 percent.

The fees that airports charge to airlines rise after airport privatizations. When the buyer is a PE firm, there is also a push to deregulate government limits on those fees. For example, after three Australian airports were privatized in the mid-1990s, the price caps governing airport revenues were replaced with a system of price monitoring that allows the government to step in if fees or revenues become excessive.

The net effect of a PE acquisition is a rough doubling of an airport's operating income, due mostly to higher revenues from airlines and retailers in the terminal rather than cost-cutting. The driving forces behind these improvements appear to be new management strategies, which likely includes greater compensation for managers, alongside investments in new capacity as well as better passenger services and technology.

Chimpanzee and Human Risk Preferences Show Key Similarities—In the world of chimpanzees, too, young males take the greatest risks, to get a better position in the hierarchy

Chimpanzee and Human Risk Preferences Show Key Similarities. Lou M. Haux et al. Psychological Science, January 3, 2023. https://doi.org/10.1177/09567976221140326

Abstract: Risk preference impacts how people make key life decisions related to health, wealth, and well-being. Systematic variations in risk-taking behavior can be the result of differences in fitness expectations, as predicted by life-history theory. Yet the evolutionary roots of human risk-taking behavior remain poorly understood. Here, we studied risk preferences of chimpanzees (86 Pan troglodytes; 47 females; age = 2–40 years) using a multimethod approach that combined observer ratings with behavioral choice experiments. We found that chimpanzees’ willingness to take risks shared structural similarities with that of humans. First, chimpanzees’ risk preference manifested as a traitlike preference that was consistent across domains and measurements. Second, chimpanzees were ambiguity averse. Third, males were more risk prone than females. Fourth, the appetite for risk showed an inverted-U-shaped relation to age and peaked in young adulthood. Our findings suggest that key dimensions of risk preference appear to emerge independently of the influence of human cultural evolution.

Discussion

Risk preference is central to human and nonhuman behavior. The current results demonstrate that chimpanzee and human risk preference share key structural similarities and converge in crucial ways. Consistent with recent findings in humans (Frey et al., 2017), our results showed that chimpanzees’ willingness to take risks appears to manifest as a traitlike preference, with high rank-order stability across a set of important domains (based on observers’ assessments) and economic choice behavior. The social-risk domain proves to be the exception (Josef et al., 2016). Furthermore, chimpanzees are, like humans, ambiguity averse and less willing to choose options with unknown risks (Ellsberg, 1961; Trautmann & van de Kuilen, 2015). Our results indicate that males are more risk seeking than females, mirroring the same difference in human risk preference (Frey et al., 2021). Finally, chimpanzee risk taking shows an inverted-U-shaped relation to age, peaks in young adulthood, and is lower in older age—again mirroring similar trends in humans (Frey et al., 2021; Josef et al., 2016; Mata et al., 2016).

According to life-history theory, risk preference should be elevated in periods in which the goal of reproduction and associated proximal goals (e.g., gaining social status) is paramount (Stearns, 1992). Young adulthood is an indispensable transitional stage for male chimpanzees to learn the techniques of socially mature males in order to establish their own social position (Kawanaka, 1993; Watts, 2018). Consistent with the young male syndrome in humans (Wilson & Daly, 1985), our results show that male chimpanzees are especially risk prone around their 20s and particularly willing to take risks in order to get a better position in the hierarchy. Higher rank is associated with both relatively high mating (Kaburu & Newton-Fisher, 2015; Muller et al., 2011) and paternity (Boesch et al., 2006; Langergraber et al., 2013; Newton-Fisher et al., 2010; Wroblewski et al., 2009) success. Furthermore, our finding of heightened general risk tolerance during young adulthood converges with a recent overview of risk behavior in humans concluding that risk taking is heightened during emerging adulthood (Willoughby et al., 2021).

The current findings, in combination with the multimethod design, enrich the comparative approach in important ways. First, the general and traitlike preference for risk is congruent with evidence suggesting that animal personalities exist across a range of species and that risk-related traits are common characteristics (Wolf et al., 2007). Second, we found that the strangers risk domain was only weakly correlated with the other risk domains. This finding is in line with those of earlier studies indicating that trusting other individuals is not just a special case of risk taking but is based on important forms of social preferences, such as betrayal aversion (Fehr, 2009; Haux et al., 2021). Moreover, in humans, willingness to trust does not follow an inverted-U-shaped pattern but instead remains relatively stable across the adult life span (Josef et al., 2016). These results fit ideas that in humans and chimpanzees, the social domain remains prioritized across adulthood (Carstensen et al., 1999; Rosati et al., 2020). Third, chimpanzees’ observed ambiguity aversion is in line with results by Rosati and Hare (2011). They found that chimpanzees and bonobos are sensitive to ambiguity in the first trials of their experiment, suggesting that subjects dislike choosing options with unknown risks. Yet it remains unclear to what extent chimpanzees knew that only probability but not the information about outcomes was missing. This raises the question of whether ambiguity attitudes in Ellsberg’s (1961) implementation of the construct can be measured in nonverbal populations.

Fourth, our results suggest that chimpanzees are risk neutral to (minimally) risk prone. Past research offers inconsistent findings in this regard. The variation in risk sensitivity in studies may be explainable in terms of the presentation and experience of probabilities (see Hau et al., 2010; Heilbronner & Hayden, 2016; Hertwig, 2015; Wulff et al., 2018), that is, whether decisions were based on experienced frequencies (see Calcutt et al., 2019; Haux et al., 2021; Heilbronner et al., 2008; Keupp et al., 2021), or whether subjects had to infer probabilities from the task design (see Haun et al., 2011; Rosati & Hare, 2011, 2012, 2013, 2016). Furthermore, the possibility of coming away empty-handed—whether the risky option included the possibility of receiving nothing or always provided at least some amount of food—could also alter the decision (see Haux et al., 2021; Keupp et al., 2021).

Finally, the relatively small sample sizes and the concomitant sex and age distributions of past studies limit the generalizability of previous findings. Future research should expand the multimethod approach, for instance, by including several behavioral measures. This would allow researchers to examine the causes behind the variation in previous work and delineate which task characteristics influence chimpanzee risk sensitivity. Studies involving chimpanzees from different groups and environments will further enrich the discussion about the generalizability of behavioral variations. Because of their early-life experiences, sanctuary chimpanzees might display different risk preferences and behavior from those living in zoos and those in the wild (for a discussion on the generalizability across groups, see King et al., 2005; Laméris et al., 2021; Lutz et al., 2022; Weiss et al., 2007; Wobber & Hare, 2011). Last but not least, because it has been proposed that bonobos (Pan paniscus) and chimpanzees (humans’ two closest living relatives) show divergent risk preferences (see Rosati, 2017), for a complete reconstruction of our last common ape ancestors preferences, it is essential to also study bonobos’ willingness to take risks in more depth in the future.

In the behavioral sciences, risk preference is a mainstay of and a key building block in theories of choice (Barseghyan et al., 2013; Brailovskaia et al., 2018; Clark & Lisowski, 2017; Dohmen et al., 2011; Mata et al., 2018; Schonberg et al., 2011; Slovic, 1987). In recent years, the measurement and stability has been central to the debate about the nature of risk preferences (Frey et al., 2017, 2021; Josef et al., 2016; Schildberg-Hörisch, 2018; Weber et al., 2002). Our multimethod approach can enrich this discussion, indicating that across various aspects of risk preference, both observer ratings (for a discussion on the validity of human ratings, see the Supplemental Material) and behavioral choices are directionally consistent. These findings offer an important first step toward a general mapping of the construct of risk preference in chimpanzees. Understanding the degree of temporal stability and systematic individual change in chimpanzee risk preference will be an important endeavor for future research (Schildberg-Hörisch, 2018). In addition, “actuarial” data such as the frequency of injuries from hierarchy fights will offer another important addition to a multimethod approach to study risk preference in chimpanzees.

In humans, scholars have proposed that the willingness to take risks and to trust others is transmitted across generations through socialization experiences (Dohmen et al., 2012; Roberts et al., 2005; Slovic, 1966) but is also subject to genetic influences (Karlsson Linnér et al., 2019). Our findings suggest that human risk preference may in addition also have deeper phylogenetic roots than previously suspected. Structural similarities in risk preferences of humans and one of our closest living relatives are likely to reflect adaptations to similar dynamics in primate life histories.