Widely cited psychology study, suggesting that winners of competitions are more likely to cheat subsequently, fails to replicate

Does competitive winning increase subsequent cheating? Andrew M. Colman, Briony D. Pulford, Caren A. Frosch, Marta Mangiarulo and Jeremy N. V. Miles. Royal Society Open Science, Volume 9, Issue 8, August 3 2022. https://doi.org/10.1098/rsos.202197

Abstract: In this preregistered study, we attempted to replicate and substantially extend a frequently cited experiment by Schurr and Ritov, published in 2016, suggesting that winners of pairwise competitions are more likely than others to steal money in subsequent games of chance against different opponents, possibly because of an enhanced sense of entitlement among competition winners. A replication seemed desirable because of the relevance of the effect to dishonesty in everyday life, the apparent counterintuitivity of the effect, possible problems and anomalies in the original study, and above all the fact that the researchers investigated only one potential explanation for the effect. Our results failed to replicate Schurr and Ritov's basic finding: we found no evidence to support the hypotheses that either winning or losing is associated with subsequent cheating. A second online study also failed to replicate Schurr and Ritov's basic finding. We used structural equation modelling to test four possible explanations for cheating—sense of entitlement, self-confidence, feeling lucky and inequality aversion. Only inequality aversion turned out to be significantly associated with cheating.

3. Discussion

Schurr & Ritov's [1] experiments were severely underpowered and vitiated by other design and methodological problems. In particular, their basic finding that competitive winning is associated with subsequent cheating was based on a study in which participants were not assigned randomly to experimental and control treatment conditions. Our study 1 replicated Schurr and Ritov's study as closely as possible with adequate power and random assignment to experimental and control conditions. We observed significant levels of cheating in both experimental and control conditions but failed to replicate Schurr and Ritov's basic finding of higher cheating by winners, although the experimental manipulation of winning or losing in both of our experiments was identical to Schurr and Ritov's. We also found no evidence for any significant effect of competitive losing on cheating in the subsequent game of chance.

In study 2, we tested the hypotheses that competitive winning or losing is associated with subsequent cheating in an even larger experiment, conducted online, with participants assigned randomly to winning, losing, paired control, and unpaired control treatment conditions. Once again, we observed significant levels of cheating in all treatment conditions but found no evidence to support the hypotheses that either winning or losing is associated with subsequent cheating. There was no significant difference in cheating between our paired and unpaired control conditions—whether cheating was associated with money being taken from another participant or from the experimenter.

This study also included an investigation, using SEM, to test the hypotheses that winning is associated with a latent variable that we labelled 'pride', indicated by self-confidence, a feeling of luckiness, and a sense of entitlement, and that pride is associated with subsequent cheating, or that losing is associated with a latent variable of 'shame', indicated by a sense of entitlement and inequality aversion, and that shame is associated with subsequent cheating. We measured all the indicator variables with psychometric scales that showed high reliability in our study, and the only significant association that emerged was between inequality aversion and cheating. This suggests that participants who were least inequality-averse were most likely to cheat in the coin-flip game, whether they had won or lost the previous competitive perceptual task. The association of inequality aversion with cheating was not strong, but it is worth investigating experimentally. It may reflect a more general sense of fairness among participants who are inequality averse. If those who value fairness strongly tend to be inequality averse and also construe cheating as a form of unfairness, the association would be explained, but that explanation requires further experimental evidence.

One key question that needs to be addressed is why the results of both of our studies failed to replicate Schurr & Ritov's [1] basic finding that competitive winning is associated with subsequent cheating in a game of chance. One possibility is that Schurr and Ritov's finding, based as it was on a severely underpowered study without proper random assignment to experimental and control groups, cannot validly be inferred from their results. A second possibility relates to their unusual methodology, in which half the participants in every testing session were randomly assigned as passive participants, whose only role was to receive the money that the other half—the active participants—left behind after taking what they claimed was owing to them after the dice game. In our studies, the participants were told that the money that they left behind would go to ‘the other person you are paired with’, with the implication that it was one of the other participants, and in that sense, from the participants' point of view, it was similar to what Schurr and Ritov's participants believed. However, the active participants in Schurr and Ritov's experiment believed that the money they left would go to others who had done absolutely nothing in the experiment, whereas the participants in our replications could have believed that the money would go to others who were fully participating. All of Schurr and Ritov's participants who rolled the dice were told that ‘The rest of the money will go to one of the participants sitting in the lab who did not play the two-dice-under-a-cup game’ [1, p. 1757]. This might possibly explain the failure of our experiments to replicate Schurr and Ritov's basic finding if their winners, in contrast to ours, believed that the recipients of money left behind were more deserving of being cheated, but that would suggest that the basic finding applies only in the artificial context of their experimental setup or in very limited and unusual circumstances. In everyday life, people who cheat rarely, if ever, know that their victims have done nothing to earn the money out of which they are being cheated. A third possibility is that the discrepancy between Schurr and Ritov's findings and ours arises from a cross-cultural difference between students in Israel and the UK; but we are unaware of any evidence that might support that interpretation, it is very unlikely given that Israel and the UK are both WEIRD (western, educated, industrialized, rich, democratic) cultures [36], and if correct it would severely limit the generality of Schurr and Ritov's basic finding (and also, by symmetry, our own basic finding).

Given the published evidence that more cheating tends to occur in online than laboratory studies [26,27], it is worth noting that we found no such difference. In study 1, incentives were lower than in study 2 and participants cheated, on average, by 31p out of a possible maximum of £3.00 (10.3%), while in study 2 they cheated by £3.25 out of a maximum of £50.00 (6.5%). The incentives were much greater in study 2, therefore participants' cheating translated into greater monetary terms in study 2. In our laboratory-based study 1, using Cohen's [11] index of effect size, the overall effect size of cheating was d = 0.46 and in our online study 2 it was d = 0.42. The finding of such a negligible difference can perhaps be explained by the fact that the dice-under-a-cup game that we used in the laboratory in study 1 provides an opportunity for cheating that seems almost entirely ‘safe’, in the sense that it would be impossible to detect a particular instance of cheating. If that interpretation is right, then our online experiment, in which the corresponding task was a coin-flip task, may not have provided a significantly greater sense of security, and participants may have felt equally disinhibited from cheating in both experiments. Thus the general cheating that we found across all conditions would be in line with recent evidence that cheating tends to occur particularly when it is unobservable by the experimenters [37].

Our studies have not provided much enlightenment as to what leads some people to cheat. In both studies, cheating occurred at a low but significant level in all treatment conditions, and the only psychometric variable that correlated significantly with cheating was inequality aversion. Our SEM revealed only one path that reached statistical significance, from shame to number of heads claimed and hence cheating. One of the indicators of shame was inequality aversion. Further research is clearly required to determine whether inequality aversion is indeed causally related to cheating and if so why. One possibility is that inequality aversion is associated with a more general concern for fairness and that people who value fairness are less likely to cheat because they perceive cheating as a form of unfairness, but without further evidence this interpretation remains speculative.

The aim of study 2 was to discover variables, possibly but not necessarily including competitive winning or losing, that might explain cheating in a subsequent game of chance. The SEM should reveal whether, and if so how, winning or losing is implicated. We hypothesized that sense of entitlement, self-confidence, personal luckiness and inequality aversion might help to explain cheating. For example, if Schurr & Ritov [1] were right, then winning should be associated with sense of entitlement and sense of entitlement should be associated with cheating. Sense of entitlement is interpreted by the authors of the scale that we used to measure it [31] as a personality trait, and we should perhaps expect a personality trait to be largely unaffected by an experimental manipulation such as winning or losing. However, the SEM does not require winning or losing to play any part in the potential relationship of any of the other variables to cheating. For example, we might have found that trait sense of entitlement is associated with cheating, irrespective of any association with winning or losing, just as we did, in fact, find that inequality aversion is associated with cheating without any significant association with winning or losing.

 

Contra Saez, Piketty et al., in a world in which ideas drive GDP, maximizing the welfare of the middle class and below requires a lower, not higher top tax rate

Taxing Top Incomes in a World of Ideas. Charles I. Jones. Journal of Political Economy, Aug 2022. https://doi.org/10.1086/720394

Abstract: This paper considers top income taxation when (i) new ideas drive economic growth, (ii) the reward for successful innovation is a top income, and (iii) innovation cannot be perfectly targeted by a research subsidy—think about the business methods of Walmart, the creation of Uber, or the “idea” of Amazon. These conditions lead to a new force affecting the optimal top tax rate: by slowing the creation of new ideas that drive aggregate GDP, top income taxation reduces everyone’s income, not just income at the top. This force sharply constrains both revenue-maximizing and welfare-maximizing top tax rates.

Abstract of a 2019 version, which refers to Saez by name: This paper considers the taxation of top incomes when the following conditions apply: (i) new ideas drive economic growth, (ii) the reward for creating a successful innovation is a top income, and (iii) innovation cannot be perfectly targeted by a separate research subsidy --- think about the business methods of Walmart, the creation of Uber, or the "idea" of Amazon.com. These conditions lead to a new force affecting the optimal top tax rate: by slowing the creation of the new ideas that drive aggregate GDP, top income taxation reduces everyone's income, not just the income at the top. When the creation of ideas is the ultimate source of economic growth, this force sharply constrains both revenue-maximizing and welfare-maximizing top tax rates. For example, for extreme parameter values, maximizing the welfare of the middle class requires a negative top tax rate: the higher income that results from the subsidy to innovation more than makes up for the lost redistribution. More generally, the calibrated model suggests that incorporating ideas as a driver of economic growth cuts the optimal top marginal tax rate substantially relative to the basic Saez calculation.

[Some can admit to the unavoidability of going downwards, to a less rich world, if we want to redistribute and have no upper class...: Revolutionaries in societies that used 1/4 as much energy as we do thought communism right around the corner; let's get the abundance that matters (everyone be free to pursue learning, play, sport, amusement, companionship, & travel) https://www.bipartisanalliance.com/2019/05/revolutionaries-in-societies-that-used.html]

1. Introduction

This paper considers the taxation of top incomes when the following conditions apply: (i) new ideas drive economic growth, (ii) the reward for creating a successful new idea is a top income, and (iii) innovation is broad-based and cannot be perfectly targeted by a separate research subsidy.

The classic tradeoff in the optimal taxation literature is between redistribution and the incentive effects that determine the “size of the pie.” But in most of that literature — starting with Mirrlees (1971), Diamond (1998), Saez (2001) and Diamond and Saez (2011) — the “size of the pie” effects are relatively limited. In particular, when a top earner reduces her effort because of a tax, that reduces her income but may have no or only modest effects on the incomes of everyone else in the economy.

In constrast, I embed the optimal tax literature in the idea-based growth theory of Romer (1990), Aghion and Howitt (1992), and Grossman and Helpman (1991). According to this literature, the enormous increase in living standards over the last century is the result of the discovery of new ideas — perhaps by a relatively small number of people. To the extent that top income taxation distorts this innovation, it can impact not only the income of the innovator but also the incomes of everyone else in the economy.

The nonrivalry of ideas is key to this result and illustrates why incorporating physical capital or human capital into the top tax calculation is insufficient. If you add one unit of human capital or one unit of physical capital to an economy — think of adding a computer or an extra year of education for one person — you make one worker more productive, because these goods are rival. But if you add a new idea — think of the computer code for the original spreadsheet or the blueprint for the electric generator — you can make any number of workers more productive. Because ideas are nonrival, each person’s wage is an increasing function of the entire stock of ideas. A distortion that reduces the production of new ideas therefore impacts everyone’s income, not just the income of the inventor herself.

A standard policy implication in this literature is that it may be optimal to subsidize formal R&D, and one could imagine subsidizing research but taxing top incomes as a way to simultaneously achieve both efficient research and socially-desirable redistribution. Instead, we consider a world with both basic and applied research. Basic research uncovers fundamental truths about the way the world works and is readily subsidized with government funding. Applied research then turns these fundamental truths into consumer products or firm-level process innovations. This is the task of entrepreneurs and may not be readily subsidized as formal R&D. Think about the creation of Walmart or Amazon.com, organizational innovations in the health care and education industries, the latest software underlying the Google search engine, or even the creation of nonrival goods like a best-selling novel or the most recent hit song. Formal R&D is a small part of what economists would like to measure as efforts to innovate. For example, around 70% of measured R&D occurs in the manufacturing industry. In 2012, only 18 million workers (out of US employment that exceeds 130 million) were employed by firms that conducted any official R&D. 1 According to their 2018 corporate filings, Walmart and Goldman-Sachs report doing zero R&D.

The idea creation and implementation that occurs beyond formal R&D may be distorted by the tax system. In particular, high incomes are the prize that motivates entrepreneurs to turn a basic research insight that results from formal R&D into a product or process that ultimately benefits consumers. High marginal tax rates reduce this effort and therefore reduce innovation and the incomes of everyone in the economy. Taking this force into account is important quantitatively. For example, consider raising the top marginal tax rate from 50% to 75%. As we discuss below, in the United States, the share of income that this top marginal rate applies to is around 10%, so the change raises about 2.5% of GDP in revenue before the behavioral response. In the baseline calibration, such an increase in the top marginal rate reduces innovation and lowers GDP per person in the long run by around 6 percent. With a utilitarian welfare criterion, this obviously reduces welfare. But even redistributing the 2.5% of GDP to the bottom half of the population would leave them worse off on average: the 6% decline in their incomes is not offset by the 5% increase from redistribution. In other words, unless the social welfare function puts disproportionate weight on the poorest people in society, raising the top marginal rate from 50% to 75% reduces social welfare.

We consider various revenue- and welfare-maximizing top tax rate calculations, first ignoring the effect on innovation and then taking it into account. For a broad range of parameter values, the effects are large. For example, in a baseline calculation, the revenue-maximizing top tax rate that ignores the innovation spillover is 92%. In contrast, the rate that incorporates innovation and maximizes a utilitarian social welfare function is just 22%. Moreover, if ideas play an even more significant role than assumed in this baseline, it is possible for the optimal top income tax rate to turn negative: the increase in everyone’s income associated with subsidizing innovation exceeds the gains associated with redistribution.

Importantly, however, the point of this paper is not to estimate “the” optimal top income tax rate. Such a calculation involves many additional considerations documented in the existing literature (reviewed below) that are omitted from the analysis here. Instead, the point is that future work aimed at calculating such a number will certainly want to explicitly consider the effects of top income taxation on the creation of new ideas. They appear to be quantitatively important.

The remainder of the paper is organized as follows. After a brief literature review, Section 2 lays out the steady-state of a rich dynamic growth model and considers the top tax rate that maximizes revenue, along the lines of Diamond and Saez (2011) and others. Section 3 then considers the tax scheme that maximizes the welfare of the “bottom 90%” or the median voter (they are the same people here). This turns out to matter quantitatively: the planner cares about distorting the creation of ideas not merely because it affects the revenue that can be earned by regular workers, but because it affects their consumption and economic growth directly. This setup is especially convenient for two reasons. First, it yields a nice closed-form solution. Second, it allows us to remain agnostic about the source of the behavioral tax elasticity for top earners: whether this comes from an effort choice or an occupational choice or from something else is irrelevant; we just need to know the elasticity.

Section 4 goes further and finds the tax system that maximizes a utilitarian social welfare function. While this objective function is obviously of interest, the solution does not admit a closed-form expression. In addition, we must be explicit about the nature of the behavioral tax elasticity for top earners, which makes the model less general. Section 5 discusses additional results and extensions, including empirical evidence on growth and top income taxation. Finally, Section 6 builds the full dynamic growth model that nests the simple model as a special case in the steady state. 

Research indicates that people will behave in ways that are consistent with the genes they believe they possess; it is applicable too to the context of risk-taking

Genetic Risk Information Influences Risk-Taking Behavior. Ryan Wheat, Matthew Vess and Patricia Holte. Social Cognition, Vol. 40, No. 4. August 2022. https://doi.org/10.1521/soco.2022.40.4.387

Abstract: Research indicates that people will behave in ways that are consistent with the genes they believe they possess. We examined this tendency in the context of risk-taking. We predicted that bogus genetic testing results indicating a propensity for risk-taking would cause participants to demonstrate riskier behavior. Participants submitted saliva tests and were randomly assigned to receive bogus genetic feedback indicating high propensity or low propensity for risk-taking. They then completed a standardized measure of risk-taking behavior. Results showed that those who received feedback indicating they were genetically disposed to risky behavior demonstrated higher risk-taking behavior than those who received feedback indicating that they were genetically disposed to risk aversion. These findings extend work on genetic feedback effects to a new domain and further reveal the ways that genetic feedback shapes behavior independent of one's actual genetic propensities.

Across both studies, most participants did not try to stop the staged theft or even report it to the experimenter afterward; they predicted much greater intervention in advance

See something, say something? exploring the gap between real and imagined moral courage. Nathan S. Kemper,Dylan S. Campbell &Anna-Kaisa Reiman. Ethics & Behavior, Jul 27 2022. https://www.tandfonline.com/doi/abs/10.1080/10508422.2022.2104282

Abstract: Research shows that people often do not intervene to stop immoral action from happening. However, limited information is available on why people fail to intervene. Two preregistered studies (Ns = 248, 131) explored this gap in the literature by staging a theft in front of participants and immediately interviewing them to inquire about their reasons for intervening or not intervening. Across both studies, most participants did not try to stop the theft or even report it to the experimenter afterward. Furthermore, many participants reported confusion and inattention as precursors to nonintervention, yielding insight into what inhibits moral courage.

Keywords: Moral couragemoral judgmentbehavioral experimentqualitative methods

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We observed substantial overestimation, with participants who imagined witnessing a theft being nearly ten times more likely to say they would intervene, compared to the actual rate of intervention.

Despite the declining quality of income data: While overall income inequality rose over the past five decades, the rise in overall consumption inequality was small

Consumption and Income Inequality in the U.S. Since the 1960s Bruce D. Meyer and James X. Sullivan. Journal of Political Economy, June 28, 2022. https://doi.org/10.1086/721702

Abstract: Recent research concludes that the rise in consumption inequality mirrors, or even exceeds, the rise in income inequality. We revisit this finding, constructing improved measures of consumption, focusing on ints well measured components that are reported at a high and stable rate relative to national accounts. While overall income inequality rose over the past five decades, the rise in overall consumption inequality was small. The declining quality of income data likely contributes to these differences for the bottom of the distribution. Asset price changes likely account for some of the differences in recent years for the top of the distribution.

Previous version in 2017 (with a much longer abstract): Consumption and Income Inequality in the U.S. Since the 1960s. Bruce D. Meyer & James X. Sullivan. NBER Working Paper 23655. Aug 2017. https://www.bipartisanalliance.com/2017/08/consumption-and-income-inequality-in-us.html

People relied too much on their self-perceptions, which were more negative than the impressions they made; & understood that others saw them more positively than how they saw themselves, but they did not understand the extent of this positivity

Elsaadawy, N., & Carlson, E. N. (2022). Do you make a better or worse impression than you think? Journal of Personality and Social Psychology, Aug 2022. https://doi.org/10.1037/pspp0000434

Abstract: Are people’s metaperceptions, or their beliefs about how others perceive them, too positive, too negative, or spot on? Across six samples of new acquaintances (total N = 1,113) and/or well-known acquaintances (total N = 1,336), we indexed metabias (i.e., the mean-level difference between metaperceptions and impressions) on a broad range of attributes to test: (a) how biased people are on average, (b) whether bias is pervasive or limited to particular contexts (level of acquaintanceship) or attributes (e.g., liking judgments or traits), (c) whether bias is consistent across attributes, and (d) what explains bias. On average, participants demonstrated a negative metabias on most attributes for both new and well-known acquaintances, suggesting that people generally fail to appreciate how positively they are seen by others. However, there was variability around this average such that, whereas most participants were negatively biased (48%), many were accurate (34%), and some were positively biased (18%). Bias was also consistent across traits, suggesting that knowing people’s metabias for one attribute offers some insight into their relative bias for other attributes. What explained metabias? Generally, people relied too much on their self-perceptions, which were more negative than the impressions they made, although bias for new acquaintances involved additional factors. That said, people understood that others saw them more positively than how they saw themselves, but they did not understand the extent of this positivity. These results offer a general framework for understanding metabias and add to the growing literature, demonstrating that people are not positively biased. 

Rolf Degen summarizing... Sociologists conduct comparatively very few replications, but it looks like it would turn out badly if they did

Reproducibility in the Social Sciences. James W. Moody et al. Annual Review of Sociology, Vol. 48:65-85 (July 2022). https://doi.org/10.1146/annurev-soc-090221-035954

Abstract: Concern over social scientists’ inability to reproduce empirical research has spawned a vast and rapidly growing literature. The size and growth of this literature make it difficult for newly interested academics to come up to speed. Here, we provide a formal text modeling approach to characterize the entirety of the field, which allows us to summarize the breadth of this literature and identify core themes. We construct and analyze text networks built from 1,947 articles to reveal differences across social science disciplines within the body of reproducibility publications and to discuss the diversity of subtopics addressed in the literature. This field-wide view suggests that reproducibility is a heterogeneous problem with multiple sources for errors and strategies for solutions, a finding that is somewhat at odds with calls for largely passive remedies reliant on open science. We propose an alternative rigor and reproducibility model that takes an active approach to rigor prior to publication, which may overcome some of the shortfalls of the postpublication model.

Keywords: data replication, reproducibility

Deadly fungus can multiply by having sex, which could produce more drug-resistant, virulent strains

Yue Wang, Jianping Xu. Population genomic analyses reveal evidence for limited recombination in the superbug Candida auris in nature. Computational and Structural Biotechnology Journal, 2022; 20: 3030 DOI: 10.1016/j.csbj.2022.06.030

Abstract: Candida auris is a recently emerged, multidrug-resistant pathogenic yeast capable of causing a diversity of human infections worldwide. Genetic analyses based on whole-genome sequences have clustered strains in this species into five divergent clades, with each clade containing limited genetic variation and one of two mating types, MTLa or MTLα. The patterns of genetic variations suggest simultaneous emergence and clonal expansion of multiple clades of this pathogen across the world. At present, it is unclear whether recombination has played any role during the evolution of C. auris. In this study, we analyzed patterns of associations among single nucleotide polymorphisms in both the nuclear and the mitochondrial genomes of 1,285 strains to investigate potential signatures of recombination in natural C. auris populations. Overall, we found that polymorphisms in the nuclear and mitochondrial genomes clustered the strains similarly into the five clades, consistent with a lack of evidence for recombination among the clades after their divergence. However, variable percentages of SNP pairs showed evidence of phylogenetic incompatibility and linkage equilibrium among samples in both the nuclear and the mitochondrial genomes, with the percentages higher in the total population than those within individual clades. Our results are consistent with limited but greater frequency of recombination before the divergence of the clades than afterwards. SNPs at loci related to antifungal resistance showed frequencies of recombination similar to or lower than those observed for SNPs in other parts of the genome. Together, though very limited, evidence for the observed recombination for both before and after the divergence of the clades suggests the possibility for continuous genetic exchange in natural populations of this important yeast pathogen.

4. Discussions

In this study, we analyzed the whole genome SNPs of 1,286 C. auris strains collected from across the world over the past 20+ years to investigate the potential signatures of recombination in this species. SNPs in both the nuclear and mitochondrial genomes were analyzed, both in the total sample as well as for each of the four clades where multiple strains have been sequenced. Our analyses revealed signatures of infrequent recombination in both the total sample as well as within each of the four individual clades. In addition, specific groups of SNPs, including those in genes involved in antifungal drug resistance as well as those that are shared among all four clades, were separately analyzed to help identify the potential contributors to the observed signatures of recombination. Different patterns of allelic associations were found among the sample types and between the nuclear and mitochondrial genomes. Below we discuss the main findings of our analyses and the major implications of our results.

4.1. Comparison between nuclear and mitochondrial genomes

The 1,285 genomes analyzed here represented all the strains of C. auris that have been sequenced and deposited in GenBank by researchers, up to May 2022. Multiple studies have analyzed variable numbers of strains, with the largest number of strains analyzed by Muñoz et al. [20] where 304 strains from many geographic regions were included. Most studies have focused on nuclear genomes. Analyses of nuclear genomes in those studies revealed that the global population of C. auris could be grouped into five distinct clades, with Clades I to IV represented by multiple strains in each while Clade V was represented by only one whole-genome sequenced strain (so far). However, one previous study analyzed mitogenome variations. Based on mitogenome SNPs of 130 C. auris strains, Misas et al. [69] showed that the mitogenome and nuclear genome SNPs clustered the strains into four similar clades. However, their analyses included only one Clade II strain and their results based on 10 Clade III strains from South Africa revealed no mitogenome sequence variation within Clade III. Our analyses here significantly expanded the sample sizes of all four clades with a total of 1,285 strains. While a similar pattern of sequence divergence within C. auris into five clades for both the nuclear genome and the mitochondrial genome was observed as previously reported (20,70), our analyses also revealed several notable features. Specifically, first, despite having more than twice as many strains as the earlier study (210 vs 86), we found no unambiguous SNP within the mitogenome of Clade IV, similar to that found by Misas et al. [69]. Second, the inclusion of 23 additional Clade II strains (versis one strain in the Misas et al. study) revealed no mitogenome SNP within Clade II. Third, the inclusion of 504 additional strains from more diverse geographic sources in Clade III (i.e., 514 in this study vs 10 in the Misas et al study) revealed abundant mitogenome SNPs within Clade III. Together, these analyses revealed that the amounts of sequence variations between the nuclear and mitochondrial genomes differed at both the whole species as well as within individual clades. At the whole species level, the SNP frequency in the nuclear genome was 1.876% (232,179/12.37×106), about six times of that of the mitochondrial genome (0.315%; 89/28212).

The lower observed genetic variation in the mitochondrial genome than in the nuclear genome has been reported in several other fungal species, including the human pathogen Cryptococcus gattii species complex and the ectomycorrhizal mushroom Tricholoma matsutake species complex [71], [72], [73]. However within individual clades, while two clades (Clades II and IV) showed limited to no mitochondrial SNPs (consistent with the overall pattern within the species), the remaining two clades (Clades I and III) showed greater mitochondrial SNP frequencies than their respective nuclear genomes. At present, the mechanisms for the different amounts of sequence diversity between the two genomes among the clades are unknown. The small sample size and limited ecological niches (mostly from ear discharges) might have contributed to no mitochondrial sequence variation in Clade II. However, this explanation cannot hold for Clade IV where 210 strains from four continents and a variety of human body sites were examined, similar to those of Clades I and III strains in this study (Table S1). Geographically, strains of Clades II and IV are predominantly found in East Asia and the Americas respectively while Clades I and III are predominantly from South Asia and Africa respectively. It is possible that the higher temperature and other potential environmental factors in South Asia and Africa may have contributed to the higher mutation rates in mitochondrial genomes than in nuclear genomes in Clades I and III. The mechanisms for the observed divergent mitochondrial vs nuclear genetic variations among the four clades within C. auris remain to be elucidated.

4.2. Evidence of recombination

At both the species and individual clade levels, though the frequencies were generally low, evidence for PI was observed in both the nuclear and the mitochondrial genomes, with a significant proportion of those PI SNP pairs also in linkage equilibrium. However, the frequencies of PI SNP pairs differed among the samples. Overall, the frequency of nuclear PI SNP pairs at the species level was from twice to over 30 times of those within individual clades (Table 3, Table 4). A similar pattern was also observed for the mitochondrial genome SNPs. Together, these results suggested that there was more frequent recombination before the divergence of the clades than after individual clades were established. Specifically, though signatures of recombination were also detected within each of the four clades after their respective divergence, clonal reproduction and expansion seemed more dominant in natural populations of C. auris after the divergence of clades than before their divergence. Our observed pattern is largely consistent with the expectations of each clade having only one mating type and therefore less likely to mate and recombine among strains of the same clade.

Relative to the frequent reports of recombination in the nuclear genomes of fungal populations, reports of mitochondrial genome recombination are still rare. However, the list of fungal species and populations showing evidence of mitogenome recombination is growing. For example, since 1998, mitochondrial DNA recombination has been reported for the honey mushroom Armillaria gallica [74], the commercial button mushroom Agaricus bisporus [75], the wild ectomycorrhizal mushroom Russula virescens species complex [76], and the opportunistic human fungal pathogen Cryptococcus gattii species complex [71]. In the commercial mushroom A. bisporus, the observed frequency of mitochondrial loci with PI was correlated with the life cycles of two varieties within the species, with the outcrossing heterothallic population showing more evidence of mitochondrial genome recombination than the secondarily homothallic populations [75].

Because the ancestral population of C. auris contained strains of both mating types, evidence for recombination in the total sample was expected. The higher rate of SNP pairs that showed evidence for PI than those within individual clades is consistent with sexual recombination in the ancient population of this species. The absence of incongruent relationships among clades between nuclear and mitochondrial genome phylogenies is consistent with the absence of mating and recombination among the four clades after their divergence from each other. However, the observed PIs among SNP pairs within individual clades after their divergence are puzzling. Specifically, each clade is known to contain strains of only one mating type, MTLa for Clades I and IV, and MTLα for Clades II and III. In addition, we found limited evidence of parallel mutations in the genes that are most likely under parallel selective pressure, the antifungal drug resistance-related genes. While we cannot completely exclude the possibility that convergent mutations might have contributed to some of the observed PIs, our analyses revealed that even if they existed, such an effect would likely be minimal. However, evidence for recombination have been found in natural fungal populations known to contain only a single mating type. For example, same-sex mating has been reported in the human fungal pathogen Cryptococcus neoformans species complex and such mating can generate genetic recombinants, similar to what have been reported for opposite-sex mating and to natural populations containing strains of both mating types [77]. It is possible that low-frequency same-sex mating could have similarly happened to the individual C. auris clades to generate the observed PIs and linkage equilibrium. Alternatively, low frequency strains of the alternative mating type may exist within each of the four clades in nature and mating between strains of opposite mating types could have generated the observed signatures of recombination. Indeed, these two possibilities are not mutually exclusive, and both could have contributed to the observed signatures of recombination. Broader and more intensive sampling as well as experimental investigations of genetic crosses are needed in order to test these two possibilities.

4.3. Genes adjacent to clade-shared SNPs

Our analyses revealed three clade-shared SNP regions, with SNPs in two of these regions showing high frequency of PI with other SNPs in the genome. Interestingly, all three clade-shared SNP regions are in intergenic regions between genes coding for hydrolases, oxidoreductases, and transcription factors with potential impacts on cell growth and lifespan (Table 7). For example, the ortholog of B9J08_000508, the downstream gene of clade-shared SNP region 1, is known to regulate the target of rapamycin complex 1 (TORC1) signaling. TORC1 is a multiprotein signaling complex functions as the organizer that incorporate internal and external cues to regulate cell growth and cell cycle progression [78]. A recent study demonstrated that TORC1 signaling plays an important role in controlling NaCl resistance through Sir2 in Saccharomyces cerevisiae [79]. The clade-shared SNPs within the upstream region of TORC1 gene may be involved in regulating the expression levels of TORC1.

Interestingly, the downstream gene of clade-shared SNP region 2, B9J08_002254, codes for a protein containing a putative FMN-binding domain which is known to be most frequently found in bacteria. It has been hypothesized that proteins containing such a domain in fungi may have been horizontally transferred from bacterial to fungal genomes [80]. Indeed, multiple independent transfers of such genes and the associated upstream sequences from bacteria to strains of C. auris in different clades could have contributed to the observed distributions of clade-shared polymorphisms and PIs. Our BLAST searches revealed that based on the amino acid sequence, the closest match to B9J08_002254 was in the bacterial genus Achromobacter, with a 99% query coverage and an E value of 1e-54.

The two genes located upstream and downstream of the clade-shared SNP region #3 were B9J08_003771 and B9J08_003772. Gene B9J08_003771 has a predicted unfolded protein-binding activity, while B9J08_003772 has a predicted DNA-binding transcription factor activity, zinc ion binding activity, and transcriptional regulation activity. The unfolded protein response is known to help human fungal pathogens survive in the host through balancing the load of proteins entering the endoplasmic reticulum and the protein-folding capacity of the organelle [81]. For example, in C. albicans, the zinc finger protein CZF1 is one of the DNA-binding proteins of the Cys6Zn2 class of transcriptional regulators with a multitude of functions such as biofilm induction, hyphal growth regulation, white-opaque switch, and yeast cell adherence [82], [83], [84], [85], [86]. While functionally likely important, how the polymorphisms in the intergenic regions of these two genes contribute to strain and population fitness remains to be investigated.

4.4. Conclusions and perspectives

This study identified limited but unambiguous evidence of recombination in both the total sample and within individual clades. In addition, evidence of recombination was found in both the nuclear and mitochondrial genomes, as well as between the nuclear and mitochondrial genomes. Overall, signatures of recombination were more prominent in the total sample than within individual clades, consistent with greater frequencies of recombination before the divergence of the four clades than after their divergence. At present, while several possibilities were suggested, the mechanism(s) for the observed recombination is not known. Nevertheless, the signatures of recombination identified here suggested a number of avenues from which further investigations could be conducted, including more extensive sampling for alternative mating types within each clade, laboratory attempts of both same-sex and opposite-sex mating, and identifying the adaptive significance of clade-shared SNPs. Such investigations should allow us to better understand the genetic architecture of virulence and drug resistance evolution within and among the divergent clades of this pathogen in natural and clinical environments.

Did pollination exist before plants? Yes, some seaweeds depend on crustaceans for fertilization

Did pollination exist before plants? Research shows that seaweeds depend on crustaceans for fertilization. Jeff Ollerton, Xong-Xi Ren. Science Vol 377, Issue No. 6605, Jul 28 2022, pp. 471-472. DOI: 10.1126/science.add3198

Abstract: The sexual reproduction of seed plants involves the transfer of male gametes—in pollen—to their female gametes. In flowering plants (angiosperms), this is performed with the stigma of flowers, whereas the gymnosperms (such as conifers and cycads) produce a diversity of structures on their reproductive axes to accomplish the same task. This transfer of male gametes is generally known as “pollination” and can be mediated by animals, wind, or water. Animal pollination, principally by insects, is the dominant strategy for angiosperms but also occurs in the extant gymnosperms, as well as some species of mosses. Outside of these plants, no other group of organisms has been demonstrated to interact with animals in this way, until now. On page 528 of this issue, Lavaut et al. (1) demonstrate that a living species of red seaweed, Gracilaria gracilis, uses the isopod crustacean Idotea balthica to transfer its male gametes, substantially extending the phylogenetic scope of species that use animals as pollinators.

A review of the genetic basis of problematic Internet use

A review of the genetic basis of problematic Internet use. Anna Maria Werling, Edna Grünblatt. Current Opinion in Behavioral Sciences, Volume 46, August 2022, 101149. https://doi.org/10.1016/j.cobeha.2022.101149

Highlights

• PUI is an increasing problem in mental health around the globe.

• PUI shares some clinical similarities with other substance-related disorders.

• Candidate genes of the serotonergic and dopaminergic pathways have been found in PUI.

• Promising multifaceted approaches, include genotyping/phenotyping, and polygenetics.

• Transcriptomics and epigenomics may support research, expanding the knowledge of PUI.

Abstract: Problematic Internet use (PUI) has become of increasing interest in mental health. Despite the rising number of PUI in all ages, the exact underpinning etiology is still missing. There is increasing evidence that, in particular, genetic, environmental, and personality factors are involved in the development and maintenance of PUI. However, the neurobiological mechanism of PUI has not been yet extensively investigated, and still reports conflicting results. Previous studies have focused on candidate genes, mainly of the serotonergic, dopaminergic, or acetylcholinergic pathways known partly as risk factors in other substance-use disorders. This review focuses on preexisting literature on the genetic basis of PUI, and implications for future research approaches to fill the gap of its etiology. Understanding the exact etiology and potential genetic mechanism is the basis for a better understanding of PUI and future therapy implications.

Keywords: Problematic Internet useInternet-use disorderInternet addictiongaming disordergambling disordergenegeneticsenvironmentgenome-wide association studySNPstranscriptomicepigenomicpolygenic risk factorbehavioural traitsepigenetic

Genetic evidence for problematic Internet use

PUI is regarded as a multidimensional syndrome with overlapping symptoms for substance-related and addictive disorders [1] and impulse-control disorders 11, 124, 130. The syndrome comprises characteristic symptoms, such as impaired control about the use of the Internet, mental engagement with the Internet, symptoms resulted by reduced use such as craving and withdrawal, increasing the amount of use, failed attempts to reduce the Internet use, lying about the extent of the use, loss of interest in activities, difficulties with relationships, and negative psychosocial consequences (e.g. 11, 42, 133, 158, 157). Recently, two new diagnoses of behavioral addictions were added to Chapter 6 of ICD-11 [147]: GD and gambling disorder. Both diagnoses are characterized by a persistent or recurrent pattern of gaming behavior online or offline. Additionally, all three criteria have to be fulfilled, impaired control over play, priority of games over other interests and activities of life, and continuation of gaming, despite negative consequences and impairments in various life areas. Furthermore, the pattern of gaming has to be seen for at least for 12 months, or less when the symptoms are severe. These criteria seem to have been used to date as a blueprint for other PUI behaviors, and in genetic studies. Owing to its above-mentioned characteristic symptoms for alcohol or drug addiction, experts suspect a vulnerability to PUI/IA to be associated with a genetic predisposition [130]. However, in contrast to other forms of addictive behavior (such as gambling and psychoactive substance abuse), only little research has investigated genetic risk factors in PUI. However, growing evidence reveals that behavioral addictions such as IA or compulsive Internet use resemble other substance-related addictions in different views [41] and they probably share similar neurobiological underpinnings. Twin studies to date have demonstrated a moderate-to-high heritability of substance use and addiction [139]. Surprisingly, with regard to the increasing research of PUI, studies exploring the genetic background of PUI are rather limited. Up to date, only few studies have investigated the heritability in PUI 82, 84 and resulted in 40% up to nearly 70% 47, 87, 141. Based on twin studies, some individuals are more susceptible to PUI than others due to their genetic vulnerabilities. Various types of (behavioral) addictions such as substance abuse and gambling have already shown significant gene-loci association, identifying successfully genetic markers 118, 143, 49•, 61. To investigate the interplay between genetic and environmental influences, some studies also focused on specific facets as potential mediating sources such as self-directedness or self-regulation [47]. Here, the heritability varies from being negligible up to explaining 44% of the variation [47]. Other samples investigated the sole genetic role and revealed a highly genetic role up to 68% in a Turkish sample of young twin pairs [31]. Other studies also demonstrated a genetic influence with 41–48% 141, 87, or 58% in girls and 66% for boys 82, 84. Other studies investigating mobile-phone use showed moderate heritabilities for various aspects of its use (such as talk and text frequency) and varied from 34% to 60% [94] or IGD from 48% to 66% [64]. Other studies show that the heritability for compulsive Internet disorder for boys is the same with girls [141]. Interestingly, comparing heritability between adults and adolescents, heritability estimates for adults were lower, and for some assessment scales, genetic influence was even negligible compared with adolescents [47]. This shows that the genetic contribution may change over the life span.

Violence against all, pregnant women & children included: Organized violence from the rulers

This is human nature... From Maribel Fierro's Violence against women in Andalusi historical sources third/ninth-seventh/thirteenth centuries). In: Violence in the Islamic thought from the Quran to the Mongols, Robert Gleave, Istvan Kristo-Nagy, Eds. 2015. Cleaned of references:

The situation in Cordoba during the fitna barbariyya – so-called because the Cordobans rejected and fought against those caliphs who were supported by the Berbers – is described along the same lines: depravity reigned, wine was drunk publicly and adultery and sodomy were allowed. The Cordobans who showed a preference for Sulaymān al-Mustaʿīn – known as the caliph of the Berbers – were killed, together with some of the women who were with them; and other women were eventually sold as if they were prisoners of war. [...]. The caliph Muḥammad b. Hishām b. ʿAbd al-Jabbār al-Mahdī ordered the houses of the Cordoban Berbers to be pillaged and allowed their harems to be violated: women were made captive and sold in the dār al-banāt, and pregnant women were killed.

After al-Mahdī had escaped from Cordoba and was trying to recover his authority, his ally, the general Wāḍiḥ, made a pact with the Christians, according to which, among other things, the Christians were allowed to take the wives of the Berbers they defeated. When al-Mahdi returned to power, in spite of the fact that the Berbers had left Cordoba, he ordered that anybody resembling a Berber be killed, including children and pregnant women.

[...] 

Every man was killed, the harems were dishonoured and the virgins raped: blood fell down to their feet, and they were left naked and crying. The blacks and the lowest soldiers of the Zirid troops took possession of the women, so that their tents became full with them, until the Zirid king Badis took pity on them after three days. They were then left alone, naked and barefoot, and made their way to other villages and fortresses.

[...]

Captivity and enslavement were bad enough, but there was also no lack of cruelty, which is often represented when dealing with the treatment of virgins. The military leader of the Christians [...] included among the captives that were his part of the booty virgins who were eight and ten years old. The conquerors took possession of the houses with their inhabitants and all their belongings: women were raped in front of their relatives, those who were married in front of their husbands, and virgins in front of their fathers, who were powerless, because they were held in chains; Muslim women so abused were eventually passed to slaves, so that they could then take pleasure with them.

It is very difficult to know how much of this is re-writing history to make the previous ruler look bad, how much is propaganda against the religious enemies, etc. But even so, some of these things happened, probably in lesser numbers than we can read in the sources.

Individuals tend to conform to the group's moral judgments even without the presence of the group's members, but people with utilitarian inclinations conform to a greater extent and more frequently than people with deontological inclinations

The Effects of Individual Moral Inclinations on Group Moral Conformity. I. Z Marton-Alper, A. Sobeh, S.G Shamay-Tsoory. Current Research in Behavioral Sciences, July 30 2022, 100078. https://doi.org/10.1016/j.crbeha.2022.100078

Highlights

• Individuals tend to conform to the group's moral judgments even without the presence of the group's members.

• Individual's moral inclination affects their conformity tendency.

• people with utilitarian inclinations conform to a greater extent and more frequently than people with deontological inclinations.

Abstract: Conformity has been shown to affect behaviors ranging from attitudes to moral decisions. The current research examined how individual moral inclination (i.e., utilitarian vs. deontological) affects moral conformity in online settings. To this end we designed a trolley-like moral dilemma paradigm in which participants rated moral decisions both individually and after being exposed to other people's ratings. We validated the task with 363 participants, demonstrating that in online settings individuals tend to conform to the group's moral judgments. Using an additional 346 participants, we showed that individual differences influence the conformity tendency, such that people with utilitarian inclinations conform to a greater extent and more frequently than people with deontological inclinations. We conclude that people with prior utilitarian inclinations are more disposed to moral conformity.

Keywords: ConformityMoralityUtilitarianDeontologicalOnline

Adolescent and young adult daily mobility patterns were moderately to highly heritable

Individual differences in adolescent and young adult daily mobility patterns and their relationships to big five personality traits: a behavioral genetic analysis. Jordan D. Alexander et al. Journal of Research in Personality, July 29 2022, 104277. https://doi.org/10.1016/j.jrp.2022.104277

Abstract: Youth behavior changes and their relationships to personality have generally been investigated using self-report studies, which are subject to reporting biases and confounding variables. Supplementing these with objective measures, like GPS location data, and twin-based research designs, which help control for confounding genetic and environmental influences, may allow for more rigorous, causally informative research on adolescent behavior patterns. To investigate this possibility, this study aimed to (1) investigate whether behavior changes during the transition from adolescence to emerging adulthood are evident in changing mobility patterns, (2) estimate the influence of adolescent personality on mobility patterns, and (3) estimate genetic and environmental influences on mobility, personality, and the relationship between them. Twins aged Fourteen to twenty-two (N=709, 55% female) provided a baseline personality measure, the Big Five Inventory, and multiple years of smartphone GPS data from June 2016 - December 2019. Mobility, as measured by daily locations visited and distance travelled, was found via mixed effects models to increase during adolescence before declining slightly in emerging adulthood. Mobility was positively associated with Extraversion and Conscientiousness (r of 0.17 - 0.25, r of 0.10 - 0.16) and negatively with Openness (r of -0.11 - -0.13). ACE models found large genetic (A = 0.56 - 0.81) and small-moderate environmental (C of 0.12 - 0.28, E of 0.07 - 0.15) influences on mobility. A and E influences were highly shared across mobility measures (rg = 0.70, re= 0.58). Associations between mobility and personality were partially explained by mutual genetic influences (rg of -0.27 - 0.53). Results show that as autonomy increases during adolescence and emerging adulthood, we see corresponding increases in youth mobility. Furthermore, the heritability of mobility patterns and their relationship to personality demonstrate that mobility patterns are informative, psychologically meaningful behaviors worthy of continued interest in psychology.

Introduction

In many cultures, late adolescence is the first period of substantial autonomy during the lifespan. Adolescents spend less time with their parents and more time with their peers and exert far greater control over their daily lives and activities than in childhood (Steinberg & Morris, 2001). In the United States and other western countries, developmental milestones like learning to drive, beginning to work, attending college, and leaving home all take place during late adolescence and further contribute to this expansion of autonomy (Remschmidt, 1994). As adolescents grow increasingly autonomous, adolescent personality plays a greater role in their daily experiences, behavior patterns, and life experiences (Johnson et al., 2013, McAdams et al., 2013). For example, adolescent personality is predictive of engagement in social activities, academic or career aspirations, artistic expression, and interest in recreational drug use (DeYoung et al., 2008; Wrzus et al., 2013). Additionally, life events under some degree of an adolescent’s control, like school suspensions, breaking up with a romantic partner, and starting or losing a job are also significantly associated with adolescent personality (Billig et al., 1996).

As behavior patterns which emerge during adolescence, such as eating habits, exercise, substance use, and sexual decision making, are highly predictive of important health outcomes, understanding how factors like personality contribute to their development carries significant scientific and public health implications (Alberga et al., 2012, Chambers et al., 2003, Sawyer et al., 2018). Understanding how adolescents move through and engage with their environments can help scientists, clinicians, and policy makers understand risk trajectories, identify at risk individuals, and design interventions to reduce the incidence of health problems like obesity or substance use.

Psychologists have historically relied on observational, self-report-based studies to understand developmental changes in adolescent behavior patterns. Self-report surveys are efficient to administer and adaptable to a wide variety of psychological constructs; they have helped us glean important insights into how adolescents’ daily activities change and how they are influenced by factors like personality (Csikszentmihalyi et al., 2014, Wrzus et al., 2013). However, while self-report based observational studies have proven useful, they come with methodological limitations that limit our ability to draw generalizable conclusions. For instance, they do not directly measure behavior, are subject to response biases, are limited by participant self-knowledge, and are often burdensome for participants to complete (Paulus & Vazire, 2007). Additionally, observational research is prone to confounding variables which can produce spurious correlations and render interpretation particularly difficult (Grimes & Schulz, 2002).

The limitations of self-report data can in part be mitigated through additional measures which are less prone to the biases associated with self-report. Smartphone GPS data, for example, can be used to unobtrusively observe and quantify aspects of participants’ daily activities (Harari et al., 2016; Miller, 2012). Smartphone data offer standardized, objective measures of participants’ locations and movement patterns which may be useful in corroborating the findings of existing research on adolescents’ daily lives. Previous research has demonstrated that human mobility patterns can be reliably measured using GPS data (Andrade et al., 2019) and that such patterns are meaningfully related to personality and daily activities in adolescence and young adulthood. Several studies have reported relationships between daily mobility patterns and personality traits in adolescence and young adulthood (Ai et al., 2019, Alessandretti et al., 2018, Stachl et al., 2020). Additionally, mobility based measures have been used to predict adolescent psychological and health outcomes like alcohol use, affect, anxiety and depression symptoms, and sleep patterns in adolescent and college aged samples (Jacobson and Bhattacharya, 2022, Ren et al., 2022, Santani et al., 2018, Sathyanarayana et al., 2016).

However, existing research has been conducted over short time spans in relatively small samples of adolescents, and research observing mobility patterns over the course of adolescence has yet to be conducted. Hence it remains an open question how mobility patterns change during this period of growing autonomy. Such information can help inform claims about how daily life changes during adolescence and help provide further information about whether daily mobility patterns contain useful information about human behavior over longer time spans.

Such research can be further improved by using twin data, which can help us understand where individual differences in adolescents’ daily mobility patterns come from and how they are related to potential explanatory variables like personality. Twin data allows researchers to measure the extent of genetic and environmental contributions to variation in a trait or behavior. Additionally, multivariate behavioral genetic models using twin data can assess whether associations between traits result from mutual genetic or environmental influences. Hence, twin studies can help alleviate the problem of confounding variables in observational research by providing additional understanding of the nature and origins of correlational patterns: helping to parse the extent to which associations between variables are explained by genetic, shared environmental, or non-shared environmental factors (McGue et al., 2010). Twin-based analyses can thereby offer evidence for whether adolescent mobility patterns stem more from heritable traits, such as their preferences for particular activities, or from aspects of their environment, such as how many kilometers away from school they live. Furthermore, measuring the degree of overlapping genetic influences on mobility and personality can offer further insight into why mobility might be heritable, perhaps partly due to the influence of other heritable behavioral traits, like personality.

The present study thus had three primary aims. First, to assess whether changes in autonomy and daily activities which occur during adolescence and emerging adulthood are reflected in adolescent mobility patterns. Second, to investigate how changes in mobility are related to adolescent personality. Third and finally, to estimate how mobility and its relationship to personality are influenced by genetic, shared environmental, and non-shared environmental factors.