Above a threshold level of wage, an increase in intelligence is no longer associated with higher earnings

The plateauing of cognitive ability among top earners. Marc Keuschnigg, Arnout van de Rijt, Thijs Bol. European Sociological Review, jcac076, January 28 2023. https://doi.org/10.1093/esr/jcac076

Abstract: Are the best-paying jobs with the highest prestige done by individuals of great intelligence? Past studies find job success to increase with cognitive ability, but do not examine how, conversely, ability varies with job success. Stratification theories suggest that social background and cumulative advantage dominate cognitive ability as determinants of high occupational success. This leads us to hypothesize that among the relatively successful, average ability is concave in income and prestige. We draw on Swedish register data containing measures of cognitive ability and labour-market success for 59,000 men who took a compulsory military conscription test. Strikingly, we find that the relationship between ability and wage is strong overall, yet above €60,000 per year ability plateaus at a modest level of +1 standard deviation. The top 1 per cent even score slightly worse on cognitive ability than those in the income strata right below them. We observe a similar but less pronounced plateauing of ability at high occupational prestige.

Discussion

The empirical results lend support to our argument that cognitive ability plateaus at high levels of occupational success. Precisely in the part of the wage distribution where cognitive ability can make the biggest difference, its right tail, cognitive ability ceases to play any role. Cognitive ability plateaus around €60,000 at under a standard deviation above the mean. In terms of occupational prestige, it plateaus at a similar level above a job prestige of 70: The differences in the prestige between accountants, doctors, lawyers, professors, judges, and members of parliament are unrelated to their cognitive abilities.

A limitation of our study is that we do not account for effort or non-cognitive capacities—motivation, social skills, creativity, mental stability, and physical ability (Borghans et al., 2016). Cognitive ability is more relevant for some occupations than for others, and academia, for which it is arguably most relevant, is neither the best-paid nor the most prestigious professional field. Our results thus raise the question to what degree top wages are indicative of other, unobserved dimensions of ability. However, omission of effort and non-cognitive ability from the analysis is only problematic for our conclusions about the relationship between ability and success if there are theoretical arguments to be made that their effects dominate luck in the production of top income and prestige, either because their distributions have many extreme values or if there are strongly increasing returns.

Our analysis, further, is limited to a single country. Sweden may be seen as a conservative testing ground. In countries where higher education is less inclusive, one would expect an overall weaker relationship between labour-market success and ability (Breen and Jonsson, 2007). Namely, less income redistribution and steep tuition barriers to elite colleges may impede the flow of gifted individuals from lower classes into top jobs. On the other hand, higher net wages and greater social status at the top may attract more talent, and greater differentiation in college prestige elsewhere may allow firms to select on cognitive skills among those with a college degree by using elite affiliations as a proxy. Future research on different countries may seek to evaluate to what extent our findings generalize.

Third, we limit our analyses to native-born men. This is an unavoidable restriction of the data (women and immigrants were not enrolled in the military), and it is important to learn whether our findings generalize to the full working population. We invite further research that includes women and citizens from different ethnic backgrounds, and we call for careful adjustments in measuring occupational success for different cohorts in light of marked increases in female labour-force participation over time as well as in the share of the immigrant workforce and the varying disadvantages they face along different career paths in many countries. Such research could also explore potential variation in meritocracy regimes across social groups, connecting debates on gender equality and integration to quantitative studies of the relationship between success and ability.

Finally, our analysis was descriptive in nature and did not assess the proposed theoretical mechanism. An additional mechanism that may drive the plateauing of the success–ability relation at high wages is that brighter individuals select into more poorly remunerated occupational groups, even if within these groups the brightest are rewarded the highest wages. If these worse-paying jobs are of higher prestige, this could explain the weaker patterns we observed for the relationship between wage and occupational prestige. While we could not effectively explore the operation of this possible mechanism, future studies may be able to disentangle competing mechanisms through longitudinal analysis of educational and labour market trajectories.

Recent years have seen much academic and public discussion of rising inequality (e.g. Mankiw, 2013; Piketty, 2014; Alvaredo et al., 2017). In debates about interventions against large wage discrepancies, a common defence of top earners is the superior merit inferred from their job-market success using human capital arguments (Murray, 2003; Mankiw, 2013). However, along an important dimension of merit—cognitive ability—we find no evidence that those with top jobs that pay extraordinary wages are more deserving than those who earn only half those wages. The main takeaway of our analysis is thus the identification, both theoretically and empirically, of two regimes of stratification in the labour market. The bulk of citizens earn normal salaries that are clearly responsive to individual cognitive capabilities. Above a threshold level of wage, cognitive-ability levels are above average but play no role in differentiating wages. With relative incomes of top earners steadily growing in Western countries (Alvaredo et al., 2017), an increasing share of aggregate earnings may be allocated under the latter regime.

Listening to one’s most disliked music evokes a stress response that makes the whole body revolt

Merrill, Julia, Taren-Ida Ackermann, and Anna Czepiel. 2023. “The Negative Power of Music: Effects of Disliked Music on Psychophysiology.” PsyArXiv. February 2. doi:10.31234/osf.io/6escn

Abstract: While previous research has shown the positive effects of music listening in response to one’s favorite music, the negative effects of one’s most disliked music have not gained much attention. Contra to studies on musical chills, in the current study, participants listened to three self-selected disliked musical pieces which evoked highly unpleasant feelings. As a contrast, three musical pieces were individually selected for each participant based on neutral liking ratings they provided on other participants’ music. During music listening, real-time ratings of subjective (dis)pleasure and simultaneous recordings of peripheral measures were obtained. Results show that compared to neutral music, listening to disliked music evokes physiological reactions reflecting higher arousal (heart rate, skin conductance response, body temperature), disgust (levator labii muscle), anger (corrugator supercilii muscle), distress and grimacing (zygomaticus major muscle). The differences between conditions were most prominent during “very unpleasant” real-time ratings, showing peak responses for the disliked music. Hence, disliked music leads to a strong response of physiological arousal and facial expression, reflecting the listener’s attitude toward the music and the physiologically strenuous effect of listening to one’s disliked music.

Rolf Degen summarizing... Unlike a machine, in which dedicated components are entrusted with fixed functions, the brain operates more like a complex dynamic system in which changing coalitions of neurons can perform varying tasks depending on the context

Improving the study of brain-behavior relationships by revisiting basic assumptions. Christiana Westlin et al. Trends in Cognitive Sciences, February 2 2023. https://doi.org/10.1016/j.tics.2022.12.015

Highlights

The study of brain-behavior relationships has been guided by several foundational assumptions that are called into question by empirical evidence from human brain imaging and neuroscience research on non-human animals.

Neural ensembles distributed across the whole brain may give rise to mental events rather than localized neural populations. A variety of neural ensembles may contribute to one mental event rather than one-to-one mappings. Mental events may emerge as a complex ensemble of interdependent signals from the brain, body, and world rather than from neural ensembles that are context-independent.

A more robust science of brain-behavior relationships awaits if research efforts are grounded in alternative assumptions that are supported by empirical evidence and which provide new opportunities for discovery.

Abstract: Neuroimaging research has been at the forefront of concerns regarding the failure of experimental findings to replicate. In the study of brain-behavior relationships, past failures to find replicable and robust effects have been attributed to methodological shortcomings. Methodological rigor is important, but there are other overlooked possibilities: most published studies share three foundational assumptions, often implicitly, that may be faulty. In this paper, we consider the empirical evidence from human brain imaging and the study of non-human animals that calls each foundational assumption into question. We then consider the opportunities for a robust science of brain-behavior relationships that await if scientists ground their research efforts in revised assumptions supported by current empirical evidence.

Keywords: brain-behavior relationshipswhole-brain modelingdegeneracycomplexityvariation

Concluding remarks

Scientific communities tacitly agree on assumptions about what exists (called ontological commitments), what questions to ask, and what methods to use. All assumptions are firmly rooted in a philosophy of science that need not be acknowledged or discussed but is practiced nonetheless. In this article, we questioned the ontological commitments of a philosophy of science that undergirds much of modern neuroscience research and psychological science in particular. We demonstrated that three common commitments should be reconsidered, along with a corresponding course correction in methods (see Outstanding questions). Our suggestions require more than merely improved methodological rigor for traditional experimental design (Box 1). Such improvements are important, but may aid robustness and replicability only when the ontological assumptions behind those methods are valid. Accordingly, a productive way forward may be to fundamentally rethink what a mind is and how a brain works. We have suggested that mental events arise from a complex ensemble of signals across the entire brain, as well as the from the sensory surfaces of the body that inform on the states of the inner body and outside world, such that more than one signal ensemble maps to a single instance of a single psychological category (maybe even in the same context [51,56]). To this end, scientists might find inspiration by mining insights from adjacent fields, such as evolution, anatomy, development, and ecology (e.g., [123,124]), as well as cybernetics and systems theory (e.g., [125,126]). At stake is nothing less than a viable science of how a brain creates a mind through its constant interactions with its body, its physical environment, and with the other brains-in-bodies that occupy its social world.

Outstanding questions

Well-powered brain-wide analyses imply that meaningful signals exist in brain regions that are considered nonsignificant in studies with low within-subject power, but is all of the observed brain activity necessarily supporting a particular behavior? By thresholding out weak yet consistent effects, are we removing part of the complex ensemble of causation? What kinds of technical innovations or novel experimental methods would allow us to make progress in answering this question?

How might we incorporate theoretical frameworks, such as a predictive processing framework, to better understand the involvement of the whole-brain in producing a mental event? Such an approach hypothesizes the involvement of the whole-brain as a general computing system, without implying equipotentiality (i.e., that all areas of the brain are equally able to perform the same function).

Why are some reported effects (e.g., the Stroop effect) seemingly robust and replicable if psychological phenomena are necessarily degenerate? These effects should be explored to determine if they remain replicable outside of constrained laboratory contexts and to understand what makes them robust.

Given that measuring every signal in a complex system is unrealistic given the time and cost constraints of a standard neuroimaging experiment, how can we balance the measurement of meaningful signals in the brain, body, and world with the practical realities of experimental constraints?

Is the study of brain-behavior relationships actually in a replication crisis? And if so, is it merely a crisis of method? Traditional assumptions suggest that scientists should replicate sample summary statistics and tightly control variation in an effort to estimate a population summary statistic, but perhaps this goal should be reconsidered.