Tuesday, September 21, 2021

Stronger correlations between self-esteem and mate value were found for men

Digging deeper into the relationship between self-esteem and mate value. Gary L.Brase, Meghan H. Dillon. Personality and Individual Differences, Volume 185, February 2022, 111219. https://doi.org/10.1016/j.paid.2021.111219

Highlights

• Overall self-esteem (SE) is correlated with both gender and mate value (MV).

• Both SE and MV, however, are often considered multidimensional.

• The current study replicated the prior findings, extending into subscales.

• Overall scores remained strongest, consistent with sociometer theory.

• Stronger correlations between self-esteem and mate value were found for men.

Abstract: Self-esteem is correlated with both gender (women reporting lower scores on average) and mate value. Both self-esteem and mate value, however, are often measured with multidimensional scales, and the documented relationship between these overall constructs has not been studied in terms of subcomponents. Using multidimensional measures of both self-esteem and mate value, the current study (n = 192) found expected sex difference in self-esteem and a correlation with mate value. These correlations extended pervasively into subscales, with a few notable exceptions, and the strongest relationships were with the overall scale scores. These results are consistent with sociometer theory and the idea that self-perceived mate value is a component of overall self-concept and esteem. Generally stronger correlations between self-esteem and mate value were found for men, relative to women, and further research is needed to assess the generalizability of these findings across more diverse samples.

Keywords: Self-esteemMate valueSociometerMultidimensionality


No support was found for the hypothesis that social media use contributed to the level of affective polarization; instead, it was the level of affective polarization that affected subsequent use of social media

Affective polarization in the digital age: Testing the direction of the relationship between social media and users’ feelings for out-group parties. Maria Nordbrandt. New Media & Society, September 19, 2021. https://doi.org/10.1177/14614448211044393

Abstract: There is considerable disagreement among scholars as to whether social media fuels polarization in society. However, a few have considered the possibility that polarization may instead affect social media usage. To address this gap, the study uses Dutch panel data to test directionality in the relationship between social media use and affective polarization. No support was found for the hypothesis that social media use contributed to the level of affective polarization. Instead, the results lend support to the hypothesis that it was the level of affective polarization that affected subsequent use of social media. The results furthermore reveal heterogeneous patterns among individuals, depending on their previous level of social media usage, and across different social media platforms. The study gives reason to call into question the predominating assumption in previous research that social media is a major driver of polarization in society.

Keywords: Affective polarization, echo chambers, Facebook, reversed causality, social media, Twitter

Check also other literature with references: Politically partisan left-right online news echo chambers are real, but only a minority of approximately 5% of internet news users inhabit them; the continued popularity of mainstream outlets often preclude the formation of large partisan echo chambers

The study shows that starting using social media or elevating usage did not impact an individual’s level of affective polarization over time—contrary to H1 and to common assumptions. Instead, the results suggest that affective polarization affects social media usage, in line with H2, depending on the history of previous usage, as suggested in H3. These results should essentially be good news from a democratic point of view and should alleviate the widespread worry that social media is a major driver of polarization in society.

As with any study, some remaining questions and limitations need to be discussed. To start with, as others have previously noted (Prior, 2013), in strict terms, causal inferences require exogenous variation. Nonetheless, there is widespread agreement in the literature that panel data are the best non-experimental data for approaching making causal inferences (Allison, 2005: 1). Moreover, I have taken several important measures to reduce the risk of temporal and non-temporal confounders and the patterns remain the same regardless of model specification. It furthermore deserves to be highlighted that panel data often have the upper hand vis-à-vis experimental treatments in providing a picture of processes as they naturally unfold rather than in a manipulated setting.

Turning to a discussion about the measures of affective polarization and social media use; I only had access to a measure of polarization that tapped into the respondents’ sympathies for political parties, but polarization can take on many other, and perhaps more troubling, expressions. Nevertheless, to the extent that dwindling sympathies for out-group parties appear in concert with increasing inter-group hostility and distrust that follow political lines, it is arguably something we need to be wary of.

Because of data limitations, the scope of the study was furthermore limited to inferences about the average effect of/on usage of various social media platforms. This measure had the important property of providing a picture of whether social media use as such seems to be a driver of affective polarization in society from an aggregate point of view. Nonetheless, qualitative aspects, such as purpose of usage and the content users are exposed to, are likely crucial for a deeper understanding of the mechanisms through which affective polarization and social media are connected.

The study was furthermore limited to the study of one particular country. Recent evidence suggests that The Netherlands exhibits lower levels of affective polarization than most other western countries (Reiljan, 2020) possibly making it a least likely case for detecting a relationship between these. Theorizing from a comparative perspective is beyond the scope of this study, but cross-country differences should certainly be of interest to future research.

The most striking, and complex, finding of the study calls for some reflection; namely that there was heterogeneity in how polarization affected the amount of social media usage. First of all, those who were non-users to moderate users in the previous wave increased their level of Facebook use and decreased their level of Twitter use significantly as they gained more polarized attitudes. One possibility is that individuals who developed an expressive need turned to platforms such as Facebook because they judged their chances of impacting their strong-tie and weak-tie offline relationships to be greater than their chances of impacting their more distant Twitter followers. Others may increasingly have shied away from Twitter because of unease or anger as a result of exposure to polemical Twitter debate and instead resorted to platforms that allow users to take part of a larger share of apolitical content. A third possibility can also be raised. Some strongly polarized and frustrated social media users may have abandoned conventional social media platforms in favor of other more alternative and niched platforms or even abandoned them altogether (Purhonen et al., 2021). In fact, this happened among many Trump supporters following the suspension of the account @realDonaldTrump from Twitter in the aftermath of the Capitol riots on 6 January 2021. All these explanations may have some element of truth to them, but the former should be less troubling than the latter ones. For instance, people can have legitimate reasons for feeling upset. Social media doubtlessly fills an important deliberative function as an arena for people with an expressive interest “to call something to the attention of a wide audience” (Moles, 2007: 54). However, to the extent that social media increasingly becomes a megaphone for aggressive or divisive rhetoric, this is more troublesome. There is a risk that some people with an expressive need engage in a “spiral of silence” and refrain from voicing their concerns because of a worry of being subjected to resentful comments or social exclusion (Kruse et al., 2018Noelle-Neumann, 1974).

Second, according to the results, rising levels of polarization exerted a much stronger effect on previous non-users or moderate users than more regular users, in line with H3. This gives some substance to the notion that a variety of rationales besides affective polarization drives frequent usage and that everyday users are more resilient to reducing their level of usage, even if they acquire more polarized attitudes.

A final thought on perhaps the most consequential finding of the study vis-à-vis previous research; namely that increased social media use did not seem to amplify affective polarization. It is probably warranted to be skeptical of unlimited usage of social media for several reasons. For instance, it may gradually make us more tolerant of uncivil behavior, invoke unhealthy social comparison, and reduce occasions for in-depth in person contacts. Still, the results give reason to doubt the notion that elevated affective polarization is among the suggested sinister consequences. Insofar as the findings translate to other contexts as well, they suggest that social media may not be a reliable barometer for assessing affective polarization in society and that explanations for any surge of polarization should primarily be found elsewhere. This discursive correction is important because the stronger the impression that we are deeply polarized, the higher the risk that we eventually judge it as pointless to engage in cooperation and dialogue across ideological lines. This would surely be detrimental for society and for democracy. My hope is that these results spur an interest in future evaluations of the causal direction of the relationship to avoid unnecessary consequences of what may potentially be an erroneous perception.

Monday, September 20, 2021

Optimal sexual passion outcomes were found at both higher and lower levels of religiosity, whereas mid-level religiosity was associated with the less beneficial sexual passion outcomes

Religious Piety and Sexual Passion: What Is the Connection? Rebecca W. Clarke, Chelom E. Leavitt, Dean M. Busby. Journal of Sex & Marital Therapy, Sep 19 2021. https://doi.org/10.1080/0092623X.2021.1979702

Abstract: The association between religiosity and the construct of sexual passion was examined to see whether religiosity is associated with harmonious, inhibited, and obsessive sexual passion styles. Using multiple regression and checking for interactions between religiosity, gender, broad categories of religion (Catholic, other Christian, other religious, nonreligious), and the three sexual passion styles, the following associations were found: Religiosity had a significant curvilinear relationship to all three sexual passion styles, suggesting an overlap in levels of religiosity and the construct of sexual passion. Optimal sexual passion outcomes were found at both higher and lower levels of religiosity, whereas mid-level religiosity was associated with the less beneficial sexual passion outcomes. Religious men were significantly more obsessively passionate than religious women, and religious men and women were similarly high on levels of harmonious and low on inhibited sexual passion. There were no significant interactions between religiosity, broad categories of religion, and sexual passion styles. Understanding how religion and sexual passion are associated could be useful for applied researchers as well as those who work with religious individuals who want to help these individuals develop beneficial patterns of sexual passion.


How truthful is GPT-3? A benchmark for language models

TruthfulQA: Measuring How Models Mimic Human Falsehoods. Stephanie Lin, Jacob Hilton, Owain Evans. arXiv, Sep 8 2021. TruthfulQA: Measuring How Models Mimic Human Falsehoods

Abstract: We propose a benchmark to measure whether a language model is truthful in generating answers to questions. The benchmark comprises 817 questions that span 38 categories, including health, law, finance and politics. We crafted questions that some humans would answer falsely due to a false belief or misconception. To perform well, models must avoid generating false answers learned from imitating human texts. We tested GPT-3, GPT-Neo/J, GPT-2 and a T5-based model. The best model was truthful on 58% of questions, while human performance was 94%. Models generated many false answers that mimic popular misconceptions and have the potential to deceive humans. The largest models were generally the least truthful. For example, the 6B-parameter GPT-J model was 17% less truthful than its 125M-parameter counterpart. This contrasts with other NLP tasks, where performance improves with model size. However, this result is expected if false answers are learned from the training distribution. We suggest that scaling up models alone is less promising for improving truthfulness than fine-tuning using training objectives other than imitation of text from the web.

Summarized: How truthful is GPT-3? A benchmark for language models. Owain Evans. Sep 16 2021. https://www.alignmentforum.org/posts/PF58wEdztZFX2dSue/how-truthful-is-gpt-3-a-benchmark-for-language-models

3. Larger models are less truthful. 
Across different model families, the largest models were generally less truthful (Figure 2). This “inverse scaling” trend contrasts with most tasks in NLP, where performance improves with model size. For example, the 6B-parameter GPT-J model was 17% less truthful than its 125M-parameter counterpart. One explanation of this result is that larger models produce more imitative falsehoods because they are better at learning the training distribution. Another explanation is that our questions adversarially exploit weaknesses in larger models not arising from imitation of the training distribution. We ran experiments aimed to tease apart these explanations.


An attractiveness judgment for one face part can be highly predictive of the attractiveness of the whole face or the other parts

Predicting attractiveness from face parts reveals multiple covarying cues. Chang Hong Liu,Andrew W. Young, Jiaxin Li, Xinran Tian, Wenfeng Chen. British Journal of Psychology, September 20 2021. https://doi.org/10.1111/bjop.12532

Abstract: In most studies of facial attractiveness perception, judgments are based on the whole face images. Here we investigated how attractiveness judgments from parts of faces compare to perceived attractiveness of the whole face, and to each other. We manipulated the extent and regions of occlusion, where either the left/right or the top/bottom half of the face was occluded. We also further segmented the face into relatively small horizontal regions involving the forehead, eyes, nose, or mouth. The results demonstrated the correlated nature of face regions, such that an attractiveness judgment for one face part can be highly predictive of the attractiveness of the whole face or the other parts. The left/right half of the face created more accurate predictions than the top/bottom half. Judgments involving a larger area of the face (i.e., left/right or top/bottom halves) produced more accurate predictions than those derived from smaller regions, such as the eyes or the mouth alone, but even the smallest and most featureless region investigated (the forehead) provided useful information. The correlated nature of the attractiveness of face parts shows that perceived attractiveness is determined by multiple covarying cues that the visual system can exploit to determine attractiveness from a single glance.


The evidence that COVID-19 infection causes or impacts Erectile Dysfunction is compelling

The Epidemic of COVID-19-Related Erectile Dysfunction: A Scoping Review and Health Care Perspective. Tung-Chin Hsieh et al. Sexual Medicine Reviews, September 20 2021. https://doi.org/10.1016/j.sxmr.2021.09.002

Abstract

Introduction: COVID-19 infection is expected to be associated with an increased likelihood of erectile dysfunction (ED). Considering the high transmissibility of COVID-19, ED may be a concerning consequence for a large segment of the population.

Aims: To (1) summarize existing published evidence for the impact of COVID-19 on the prevalence, severity, treatment, and management of ED; and (2) identify health-related trends in the emerging literature and identify gaps in the existing research literature and make recommendations for future research needs in the area.

Methods: A scoping literature search was conducted on April 27, 2021. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Extension for Scoping Reviews (PRISMA-ScR) checklist was followed. The literature search was performed in PubMed using the terms: COVID-19, erectile, sexual, and dysfunction. A total of 693 publications were screened for relevance. Studies were appraised for their level of evidence based on study design and the rigor of methodology.

Results: The evidence that COVID-19 infection causes or impacts ED is compelling. Four topics emerged regarding the nature of the association between COVID-19 and ED: (1) the biological impact of COVID-19 infection on ED; (2) the mental health impact of COVID-19 on ED; (3) the impact of COVID-19 on the management of ED and access to ED treatment; and (4) health disparities and the impact of COVID-19 on ED. Long-term and well-designed studies are needed to clarify the extent of the impact of COVID-19 on ED. The pandemic exposed several vulnerabilities within worldwide healthcare and social systems.

Conclusion: COVID-19 has a uniquely harmful impact on men's health and erectile function through biological, mental health, and healthcare access mechanisms. As the pandemic wanes, strategies to identify long-term effects and additional health care support may be needed to adequately mitigate the impact of COVID-19 on men's health.


Sunday, September 19, 2021

A greater tendency to have negative thoughts and feelings about people with a homosexual orientation was associated with an increased likelihood of avoiding cross-sex friendships

Avoiding cross-sex friendships: The separability of people with and without cross-sex friends. Tobias Altmann. Current Psychology, Sep 19 2021. https://rd.springer.com/article/10.1007/s12144-021-02315-0

Abstract: Prior studies on individual differences in the preference for cross-sex friendships found that this preference was not normally distributed but was instead bimodal. In one group of people, the preferences for higher or lower proportions of cross-sex friendships appear to be normally distributed, whereas in a second and unexpectedly large group of people, the preference for cross-sex friends is exactly zero. If the people in the second group with no cross-sex friends at all actively avoid forming cross-sex friendships, then these individuals may be expected to differ systematically and meaningfully from individuals who report having at least one cross-sex friend. The present study tests this hypothesis. The Big Five, homophobia, physical attraction to the opposite sex, and demographic variables from a data set of 491 adult participants were used as potential predictors of group membership. Results showed that most predictors except the Big Five contributed to supporting the separability of the two groups. Findings are discussed with regard to the differentiation between close and general friends and the potential influence of cultural factors.

Discussion

The present study was designed to test the hypothesis that people who categorically avoid forming cross-sex friendships (i.e., individuals who report having no cross-sex friends) differ systematically from individuals who report having one or more cross-sex friends. This hypothesis was tested and cross-checked using person characteristics, personality characteristics, and physical attraction as potential differentiators.

Predictors of the Avoidance of Close Cross-Sex Friends

Homophobia was found to be the main determinant for avoiding close cross-sex friendships with a large effect size. A greater tendency to have negative thoughts and feelings about people with a homosexual orientation was associated with an increased likelihood of avoiding cross-sex friendships. This supports findings by Martino (2000), who stated that homophobia in men is related to a fear of appearing too feminine such that men tend to avoid close cross-sex friendships. Interestingly, Martino (2000) also found that homophobic men try to secure their views and beliefs by encouraging other men to comply with and follow their behavior. It may be interesting for future research to also explore the effects of the beliefs and attitudes of an individual’s closest friends on the friendship choices of this individual (Parker et al., 2008). Research is also needed to clarify the role of homophobia in women in general as this is still a severely understudied phenomenon (Basow & Johnson, 2000).

The second determinant in this domain was the tendency to feel physically attracted to one’s close cross-sex friends. This finding was expected and is in line with previous research (especially Bleske & Buss, 2000; Bleske-Rechek et al., 2012) that stated that physical attraction is subjectively associated with greater costs than benefits. Consistently, individuals who avoid cross-sex friendships reported more of a tendency to feel physically attracted to their cross-sex friends in the present study. Although a smaller effect, this attraction may be speculated to be a potential cause for some individuals to either approach a cross-sex peer as a potential mate or avoid the potential relationship altogether. This causal inference is of course speculative and not directly supported by the cross-sectional data from the present study.

In sum, with respect to close friends, individuals who avoid cross-sex friendships do not appear to differ with respect to the basic personality dimensions as conceptualized in the Five Factor Model or with respect to basic demographic characteristics. However, they may be described as more homophobic and as having more of a tendency to feel physically attracted to their cross-sex friends, factors that may partly explain their friendship choices.

Predictors of the Avoidance of General Cross-Sex Friends

Determinants of the avoidance of general cross-sex friends were relationship status and migration background with rather large effect sizes. As expected, individuals in a relationship were more likely to avoid forming cross-sex friendships. Such friends might be considered a relationship threat, and thus, it appears plausible that long-term changes in the friendship network favor the reduction of cross-sex friends (Bleske-Rechek et al., 2012; Milardo, 1982).

Individuals with a migration background were also more likely to avoid forming general cross-sex friendships. This finding may be explained by findings on the values of immigrants. Wakil et al. (1981) showed that immigrants in general were inclined to focus on and fortify their core values rather than adopt the values of the host country. Focusing on differences between cultures of origin, Arends-Toth and van de Vijver (2009) demonstrated that Turkish and Arabic cultures scored highest on traditional values. Considering these findings in connection with the fact that immigration in Germany is largely from Turkish and Arabic states, as was also found in the present sample, having a migration background was associated with a greater likelihood of avoiding cross-sex friends because this is an untraditional type of friendship (Bleske-Rechek et al., 2012). However, this finding was also (or perhaps even more so) expected for close cross-sex friends and not only for general cross-sex friends.

The same finding can also be interpreted from the perspective that the people without a migration background (i.e., Germans) may be more open to forming cross-sex friendships than people from other cultures. This finding might also be explained by the specifics of how friendship is defined and lived in Germany. The narrow cultural context of the present study is a noteworthy limitation (see below), and future studies are needed to understand cultural influences on cross-sex friendship formation (see Altmann, 2021).

In sum, with respect to general friends, individuals avoiding cross-sex friendships do not appear to differ with respect to the basic personality dimensions as conceptualized in the Five Factor Model or with respect to homophobia and physical attraction. However, they may also be in a relationship or may have a migration background (with respect to Germany), two factors that may also have an influence on their friendship choices.

A secondary finding of the present study is that the significant predictors differ between close and general friendships. These differences are likely due to the different procedures that must be followed to become a close or a general friend. A close friend will be selected on the basis of a person’s individual criteria, such as the tendency to avoid a particular type of person, for instance, people of the opposite sex. By contrast, a person’s general friends may likely also include the friends of one’s close friends, colleagues at work, and so forth. Here, the mechanisms of individual selection may be less effective because, for instance, (cross-sex) colleagues are harder to avoid without causing conflicts at work. Therefore, it may be the case that close friends are typically being selected from the people in one’s environment, whereas general friends are typically being accepted as the people in one’s environment. Again, this finding may also be specific to the present sample from Germany where the distinction between close and general friends is common. In other countries or cultures, this distinction may be less relevant or less common, and thus, the predictors may depend on the type of friendship only in certain cultural contexts.

Limitations

There are several limitations that have to be considered when interpreting the present findings. Three of them will be elaborated on in the following: the bimodal distribution, the sample, and the cultural context.

First, the hypothesis was based on the finding that the distribution of numbers of cross-sex friends in relation to total numbers of friends was not normal but was instead bimodal. This bimodality was indeed distinct with regard to participants’ close friends, but it was less distinct with regard to general friends. This may indicate that the tendency to avoid forming cross-sex friendships is considerably stronger with respect to one’s close friends than among one’s other or more general friends. Therefore, the latter findings may be less reliable, and the focus on participants’ close friends may be the more relevant focus. Replications are needed to confirm the validity of the present findings as well as the assumptions of bimodal distributions for both close and general friendships.

Second, the sample contained predominantly students so that findings cannot be generalized to other parts of society. Age as well as achieving a higher level of education may be associated with certain traits, such as conscientiousness and the need for cognition, which in turn may influence priorities with respect to friendship choices. The present findings are therefore limited to young and educated populations.

A third limitation lies in the narrow cultural context in which the study was conducted. As has been argued above and has often been shown in cross-cultural studies, the definitions, mechanisms, and individual experiences of friendship differ substantially between cultures (Adams & Plaut, 2003; Baumgarte, 2016; Gareis, 1995). The study was conducted in Germany so that the findings may be limited to this country or this cultural region. This limitation pertains to several aspects of the present study, such as the basic definition of friendship, what kinds of relationships are considered “friendships,” the relevance of the distinction between close and general friends, and the relevance of each predictor included in the present study. A variable to control for cultural influences was included in the model—at least it was expected to do so to some extent by capturing the potential specificity of the German culture. However, future studies could benefit from applying a more comprehensive approach to studying cross-cultural differences in cross-sex friendship formation processes.

Barbarigenesis and the collapse of complex societies: Rome and after

Jones D (2021) Barbarigenesis and the collapse of complex societies: Rome and after. PLoS ONE 16(9): e0254240, Sep 16 2021. https://doi.org/10.1371/journal.pone.0254240

Abstract: “Barbarism” is perhaps best understood as a recurring syndrome among peripheral societies in response to the threats and opportunities presented by more developed neighbors. This article develops a mathematical model of barbarigenesis—the formation of “barbarian” societies adjacent to more complex societies—and its consequences, and applies the model to the case of Europe in the first millennium CE. A starting point is a game (developed by Hirshleifer) in which two players allocate their resources either to producing wealth or to fighting over wealth. The paradoxical result is that a richer and potentially more powerful player may lose out to a poorer player, because the opportunity cost of fighting is greater for the former. In a more elaborate spatial model with many players, the outcome is a wealth-power mismatch: central regions have comparatively more wealth than power, peripheral regions have comparatively more power than wealth. In a model of historical dynamics, a wealth-power mismatch generates a long-lasting decline in social complexity, sweeping from more to less developed regions, until wealth and power come to be more closely aligned. This article reviews how well this model fits the historical record of late Antiquity and the early Middle Ages in Europe both quantitatively and qualitatively. The article also considers some of the history left out of the model, and why the model doesn’t apply to the modern world.

Opportunity costs

So far we have been considering what happened. But our model also implies something about how it happened, how a relatively small number of barbarians had an oversized impact. Specifically, in the model, the greater resources available to folk in the core under imperial rule are counterbalanced by their greater opportunity cost of fighting. This seems to be consistent with several scholarly analyses.

The Roman Empire simply became too expensive for its inhabitants, who were no longer willing to pay in blood and money for its military power [57].

Measuring resources by population and economic production, the core had a great advantage over its neighboring periphery. “There can be little doubt that the empire possessed considerably greater reserves of manpower than the barbarians” [58]. In the fifth century, when the Roman Empire fell in the west, “historians generally propose up to 100,000 for major ruling groups like the Ostrogoths or the Vandals, and around 20,000–25,000 for the adult males who made up their armies, in provinces whose indigenous populations numbered in the millions” [42]; also [57]. There were similar disproportions in the sixth century, when much of Italy fell to the Lombards, and in the ninth and tenth centuries, when Vikings raided and settled in northern Europe. Even where the barbarian fraction was arguably greater—Franks in north Gaul, Angles, Saxons, and Jutes in Britain, Slavs in the Balkans—they were still in the minority.

In other words, if all parties had realized their full military potential and put all their economic surplus into fighting, the imperial core would easily have come out ahead. But recall the paradox of power: “the battle is not always to the strong [because] in a wide range of circumstances it pays the smaller or weaker contender to fight harder” [19]. Applied to the present case, the paradox implies that what determined outcomes in the contest between rich core and poor periphery was not just the absolute resources of each, but the opportunity costs of fighting and preparing to fight.

Economic concerns were central both in imperial expansion and contraction, even if the parties involved were not keeping careful accounts, or undertaking explicit profit maximization. “The Roman emperors had at least a crude sense of the ‘marginal costs of imperialism’” [27]. When the Roman empire was expanding, the dates at which different regions were incorporated into the empire corresponded with their economic potential (Fig 6).

During periods of decline as well, considerations of costs and benefits were crucial. The Roman military suffered some major defeats, notably at Adrianople (378 CE) where the emperor Valens and two thirds of his army perished. But the more fundamental cause of the fall is that the cost of defense came to exceed what people were willing to pay. Already under the Dominate the empire offered less bang for more bucks: citizens found themselves paying higher taxes and (probably) getting less military protection. Contrary to earlier views [59], high taxes and bureaucracy do not seem to have crippled the economy, but they did undermine support for the empire [58].

In the late third and fourth centuries, the empire confronted multiple invasions, from Visigoths, Ostrogoths, Vandals, Suevi, Alans, Burgundians, and Franks. The invaders were sometimes bought off with grants of territory and a status as foederati; more often they forcibly seized what they wanted. In any case, when territory ravaged or occupied by barbarians was lost as a source of revenue, the army could no longer be paid. In less than a century the Roman empire in the West unraveled completely. After two more centuries, the empire in southeastern Europe unraveled. No decisive battle ended the empire; it became unaffordable [51].

Even after the collapse of imperial rule the old Roman elite did not just disappear: some were killed, some fled, but others remained and adapted to the new regimes. Some even flourished, although on terms dictated by their new barbarian overlords [60].

Different scholars offer differing assessments of Roman-barbarian relations in the transition. On one account, it was mostly about the art of the deal: “What we call the Fall of the Roman empire was an imaginative experiment that got a little out of hand” [61]. A more somber judgment comes from Ward-Perkins [34]: “The Germanic invaders of the Western empire seized or extorted through the threat of force the vast majority of the territories in which they settled, without any formal agreement on how to share resources with their new Roman subjects.” From our perspective, these quotations point to flip sides of the paradox of power. On one side, the paradox implies that “non-conflictual or cooperative strategies tend to be relatively more rewarding for the better-endowed side” [19], and the Roman empire, Roman elites after the fall, and Roman successor states, all showed themselves willing sometimes to bargain and collaborate with barbarian intruders. On the other side, violence and the threat of violence from those with less to lose played a determining role in the transition. The game between Romans and barbarians was not zero-sum, but it was a long way from purely cooperative.

Varieties of rent-seeking: States and migrations

Our model predicts that where there is a wealth-power mismatch between core and periphery, there will be rent seeking. The exact mechanisms are not specified by the model, but they included, at different periods, shifts in power and wealth within the Roman empire, raiding and plunder, the consolidation of barbarian confederations and kingdoms, and barbarian invasion, migration, and mass settlement. We review varieties of rent-seeking below.

Our model implies that even in the early stages, when collateral damage is slight, we should see evidence of wealth-power mismatch. In the context of the early centuries CE, this means we expect to find a mismatch within the Empire, with more developed regions increasingly specializing in producing wealth and less developed regions increasingly cultivating a military specialization.

Even before the establishment of the Principate, this dynamic was at work, as Rome extended her rule over the Mediterranean. During this period, the eastern Mediterranean, ruled by Hellenistic monarchs, was more economically developed than the Roman West. This both made the area an inviting target for conquest, and contributed to military weakness: Eastern militaries were largely mercenary, and expensive. Rome at this point depended on a cheaper army of citizen soldiers [6263].

With the establishment of the Principate, the military basis of the empire shifted to a professional soldiery committed especially to defending the frontier, often relatively removed from the civilian population. About 2/3 of state revenues, some 2–3% of gross domestic product, went to the military [27]. About half the army consisted of citizen legionaries, about half of auxiliary forces, mostly non-citizens. The regular army increasingly drew its men from the provinces, outside Italy and the more developed east.

[M]ost legionaries across the empire were of Italian origin until the reign of Claudius (AD 41–54). Through the reigns of Claudius and Nero, about half were Italian and half of provincial origin. By Trajan’s reign (AD 98–117), legionnaires from the provinces outnumbered Italians by four or five to one [64].

The auxiliary forces too came to be largely drawn from the provinces: “It is by the blood of the provinces that the provinces are won” (Tacitus in [65]).

Barbarians may have come to make up an increasing fraction of the military [6667], (but see [68]). “The spatial, social, and ethnic peripheralization of military service—a feature common to many maturing empires—not only raised the profile of frontier forces but also drew in manpower from beyond” [63]. They became increasingly numerous in the higher ranks. “By the latter half of the fourth century increasing numbers of senior officers appear with ‘barbarian,’ frequently Germanic names” [69]. In the last days of the empire in the west, supreme military command increasingly passed to generals of Germanic origin, like Arbogast, a Frank, and Stilicho, a Vandal.

Political changes accompanied the demilitarization of the imperial core and the militarization of the periphery. Emperors from Trajan and Hadrian on found themselves spending increasing amounts of time close to the frontier, and the effective capitol shifted from Rome to Milan (286 CE) and then to Ravenna (402 CE). The old Senatorial elite of Italy, the clarissimi, continued to be extremely wealthy, but were edged out politically by a new senatorial elite. The crisis of the third century and subsequent recovery partly reflected these changes. In the third century, military units on the frontiers vied with Rome, putting up a bewildering succession of barracks emperors. Eventually a more settled situation developed as one frontier region, Illyria, came to monopolize the imperial succession.

These changes within the empire can be seen as the working out of the principle of comparative advantage, with more and less developed regions coming to specialize in production and fighting respectively. This was not the conventional, peaceable version of comparative advantage. These developments, resulting from wealth-power mismatch, were about rent-seeking: capturing wealth and forestalling its capture.

In subsequent centuries, with barbarian resources increasing outside the empire, barbarian rent seeking, trading on barbarian military prowess, is increasingly evident. This took a variety of forms. Military service, raiding and plunder, and the extortion of tribute, carried out by barbarian groups of various sizes at the expense of wealthier targets, are amply attested before and after the fall of Rome. There were also changes in social organization. Barbarian polities along the frontier probably increased their size and degree of organization, and grew more formidable. “There are clear signs that some barbarian units, especially just beyond the frontier were increasing in power and stability during the fourth century” [58]. Larger groupings appearing in the early centuries CE include the Franks (“Free/wild people”), Marcomanni (“Border men”), and Alamanni (“All men”) [57]. These changes arguably resulted from the pressures and opportunities associated with proximity to a wealthy core. The changes were driven by trade and combat—offensive and defensive—with the Roman empire itself, and jostling among barbarians for access to imperial resources. They amounted, in short, to a phase of barbarigenesis. (This outline is widely but not universally accepted, see [1857587071], but see also [69] and [72]. For a similar story of barbarian agglomeration and civilized response in the Viking age, with a dynamic model, see [73].)

Most dramatically and consequentially, barbarians could secure a share in the wealth of their neighbors by moving to where the wealth was. The first millennium has traditionally been seen as the Migration Period, the age of the Völkerwanderung. Below a few remarks on a large and disputed topic:

First, migrations during this period were mostly toward regions with denser population and greater wealth (with some exceptions, like the Norse settlement of Iceland). Some migrations proceeded from outer periphery to inner periphery. The Goths expanded from the Baltic area (Wielbark archeological culture) to the north shore of the Black Sea (Cernjakov culture) and took up plundering Roman territory on the farther shores. Huns, Avars, and Magyars moved from the Eurasian steppe to the grasslands of the Great Hungarian Plain and took up plundering and extorting tribute from the empire and its territory. Other groups moving from outer to inner periphery at some point include Burgundians, Lombards, and Bulgars. Some migrations proceeded from the periphery to imperial or former imperial territory. Germanic peoples ended up ruling over most of the western empire, southern Slavs took over most of the eastern empire in Europe. Migrations were often interconnected. The early Gothic migration pressured west Germanic groups, the Huns pressured the Goths, and the Avars pressured the southern Slavs. Western Slavs moved into territory vacated by Germanic migrations. Both push and pull might be involved in the initial migration in a series. Avars, for example, were pushed to the western edge of the steppe by Turks. But the pull toward greater wealth stands out as the dominant theme in this period.

Second, the migrations entailed substantial costs. Most of the migrants were not habitual nomads. Moving to a new location, sometimes over very large distances, sometimes more than once, entailed a major reorganization of customary routines. Even for pastoral nomads, large scale moves into new territory were not an everyday occurrence. Migration could also entail challenging political transformations, including submission to new forms of authority.

Third, the migrations arguably involved the movements of large groups of men and women, not just elites or bands of soldiers. At least this is the traditional view [66], consistent with the writings of classical authors like Marcellinus Ammianus and Jordanes. However, this is an area of controversy; Halsall [58], for example, is a skeptic regarding large-scale migrations, while Heather [18] provides a nuanced defense of something closer to the traditional view.

In the future, new sources of evidence, especially studies of genetic variation, will advance this debate. For now, some preliminary results are available. The movement of Goths, including women, from the shores of the Baltic to the Black Sea is supported by genetic evidence [74], consistent with Jordanes, and contra Kulikowski [75] who argued for cultural transformation without major migration. The Anglo-Saxon invasions (unlike the later Norman invasion) had a substantial impact on the genetics of England [7677], contra the argument that Anglo-Saxonization involved only limited migration [78]. In sixth century Italy, ancient DNA from high status graves shows the central European affinities expected of Lombard invaders, while low status burials have local roots [79].

Thus the evidence to date suggests that at least some of the migrations of the Völkerwanderung were a real demographic phenomenon—less than population replacement, but more than culture shift. It looks like large groups of men and women from the barbarian periphery of Europe were paying the costs and enjoying the benefits of moving to, or close to, more central societies, and living off them.

Collateral damage

Collateral damage from wealth-power mismatch within the empire was limited and episodic, with a partial recovery following the establishment of a new equilibrium under the Dominate. In a later period, as military advantage shifted further to the barbarians outside the empire, the damage would be increasingly severe and enduring. For the barbarian invaders of the Roman empire, the goal was to acquire Roman wealth, not to destroy it. Nevertheless, without anybody intending it, the first millennium saw a lasting collapse in social complexity and a decline in wealth, resulting to a large extent from the interactions between Europe’s core and its periphery. As in our model, this happened because there was not only rent-seeking, an unproductive diversion of resources into contests, but also collateral damage, a counterproductive loss of resources.

Collateral damage, like rent-seeking, took a variety of forms. It was partly a matter of direct destruction of property and loss of life. Beyond this, the Mediterranean-centered trade network collapsed, and the advantages of a Smithian economy, with an extensive division of labor were lost [39]. Perhaps most important, institutional breakdown and the insecurity of life and property must have discouraged individuals and groups from investing in the future.

The extent of collateral damage varied, depending on the character of political institutions. In some times and places, barbarians acted as stationary bandits [80]. A stationary bandit, in contrast to a roving bandit, has an incentive to preserve the long-term productivity of his targets. The itinerant armies of the Völkerwanderung–the Visigoths shifting around the Balkans, Italy, and Spain, the Suevi and Vandals moving through Gaul and Iberia—approximated roving bandits. By the end of the fifth century, however, these groups had settled down; most of the former Roman empire in the West was divided among a handful of successor states ruled by Germanic elites. Consistent with Olson’s analysis, the new rulers were not purely predatory; they tried to maintain the traditions of Roman rule, and to enlist the collaboration of surviving Roman elites [81]. (See also [82] on the Vikings.)

The situation was complicated, however. The stationary bandits of the post-Roman world were not unitary actors [81]. The new rulers depended on the support of the barbarian rank-and-file, the military mainstay of the new kingdoms. These followers, the descendants of fractious unlettered warrior-farmers, were often unfitted and disinclined to play the role of obedient Roman-style subjects [83]. “[T]he Germanic tribes which broke apart the Western empire were not themselves capable of substituting a new or coherent political universe for it. The difference in ‘water-levels’ between the two civilizations was still too great” [84]. As a result, early barbarian kingdoms were hybrid regimes, with one legal system for Romans, another for Germans, with the latter enjoying a privileged position. The latter were also rewarded with a share of wealth at the expense of the former, either grants of land (the usual scholarly supposition [8586]) or a share of taxes [61]. In either case, central revenues were greatly reduced [87]. “Beginning in the fifth century, there was a steady trend away from supporting armies by public taxation and towards supporting them by rents derived from private landowning” [42].

In some cases, the balance between leaders and rank-and-file among the newcomers was weighted heavily toward the latter; enduring royal government was weak or nonexistent. This was particularly true where larger numbers of settlers moved shorter distances, as in Anglo-Saxon Britain, Frankish northern Gaul, and the Slavic Balkans. In these instances, the decay of Roman institutions and the decline in social complexity was particularly marked.

The collapse of social complexity in the first millennium was both cause and consequence of a decline in state capacity, collateral damage from the shift to a low-maintenance political regime that provided limited public order at a low price. “The new Germanic lords could not offer the same extensive administration to the landowners, but they did something else: they provided cheaper protection” [62]. Some early medieval kingdoms look impressive on a map, but “by the year 1000, [outside the Byzantine empire] it would have been difficult to find anything like a state anywhere on the continent in Europe” [88]. Early medieval polities are better described as realms than states [89]. Lasting recovery would wait until the rolling wave of barbarigenesis had subsided.

Political complexities: States, cycles, and borders

The discussion up to this point has related political changes to the operation of large-scale forces over the long run. Shifts in wealth and power within the Roman empire, its dissolution first in the west and then in the European east, the formation of barbarian states, and their relative weakness when it came to maintaining law and order, all resulted, we argue, from the spatial dynamics of wealth-power mismatch, of wealth production and appropriation. But states were not entirely at the mercy of larger forces; they could also be actors in their own right. Some complications resulted that fall outside our model.

In the model, decline and recovery happen smoothly. But internal factors, apart from the external stimuli we have considered so far, also contributed to the relative strength or weakness of states. In some cases these seem to have operated cyclically: the Roman empire in the west from the first to fifth century ran through a progression—stability, near collapse, partial recovery, collapse (see above)–that amounts to two up and down alternations, each lasting a few centuries. This cycle is superimposed on the long downward movement predicted by our model [90]. (The preceding rise and fall of Republican Rome is another up and down alternation.)

Boundaries between states, unrepresented in our model, also made a difference. This may be showing up in Fig 7, where there is a middle set of countries, from Bulgaria to England, for which the model is qualitatively somewhat “off.” Take England. The model predicts modest growth to the mid-first millennium, stagnation as barbarigenesis among the country’s less-developed neighbors takes a toll, and then recovery. The real story is more dramatic, probably even more dramatic, according to later research, than McEvedy and Jones’ figures imply. As part of the Roman Empire from 43 CE, Britain experienced substantial prosperity and security. The withdrawal of Roman legions after 409 CE, followed by invasions from the Continent, resulted in a major—apparently catastrophic—decline in the density of settlement and the level of material culture [91]. “In no other part of the empire was this economic simplification so abrupt and total” [42]. In some respects, the level of material culture in Britain was lower after the legions left than before they arrived! It almost looks like the model is telling a story about an alternative history in which the Romans never occupied Britain. This counterfactual southern Britain, remaining outside the Roman Empire, avoids the wild swing from prosperity to utter collapse of the real-world England. In other words, being inside and then outside the Roman limes made a difference in ways not shown in our model. Similar observations apply to Bulgaria and Yugoslavia, where the later end of Roman rule was particularly devastating, and where, as in England, barbarian invasion led to language replacement. (Also related: in Germany there are differences right up to the present between areas that fell inside and outside the limes [92]).

These complications do not overturn the account given here, but they suggest that our model might usefully be supplemented by models of internally-driven secular cycles [90] and imperiogenesis [9]. These models do not capture the dynamics of barbarigenesis and its consequences that we explore here; they are complementary to the present effort.

Geographic complexities: Rivers and mountains, steppe, and a sheltered zone

Other potential complications left out of our model involve geographic variation. In the Results section we run the model assuming uniform geography, and then look at deviations from the model as a secondary phenomenon. The deviations largely make sense, reflecting the impacts of waterways and mountainous terrain, and the availability of arable land (with Greece as something of a special case).

For much of the rest of Eurasia, the uniform geography assumption wouldn’t work even as a rough first approximation. In the region from the Middle East through Central and South Asia to China, the division between steppe and desert on the one hand and areas of rain-fed and irrigation agriculture on the other hand was a decisive fact. Throughout this expanse, where pastoral nomads had agrarian states for neighbors, barbarigenesis took place, with the emergence of wealth-power mismatches, and the formation of states driven by external threats and opportunities [9395]. Because the border between periphery and core was the product of a climatically-dictated resource gradient between steppe and sown, the historical dynamics were different here from post-Roman Europe; this is a topic for another occasion.

Finally, where the geography of barbarians and decline and fall is concerned, the fate of the empire in the east seems to be the exception that proves the rule. In the Roman west—as in our model of barbarigenesis—the wealth of the core was up for grabs. In the east, by contrast, most of the core resource base was more secure. The European provinces of the eastern empire experienced a slew of barbarian invasions, by Visigoths (late fourth century), Huns (mid fifth century), and Ostrogoths (late fifth century). As in the west, these resulted in extensive destruction. But most of this area remained under Roman rule for several centuries longer than in the west. A key difference is that the eastern Roman empire was able to draw on the resources of a hinterland in Asia Minor, the Near East, and Egypt that was almost invulnerable to barbarians based in Europe. Constantinople, too, proved exceptionally resistant to siege. The eastern empire thus managed to sustain relative prosperity in Asia and Egypt and to tap their wealth to maintain imperial rule (albeit with less security and prosperity) in the Balkans and even to restore it temporarily to Italy and North Africa. At least for time: when, in the seventh century, most of the wealthy provinces of Asia and Africa were lost to Persian and then to Arab empires, the east Roman state lost some 4/5 of its revenues [63]. Most of Italy fell to the Lombards, and the Balkans to Avars and Slavs.