When someone violates a social norm, others may think that some sanction would be appropriate. We examine how the experience of emotions like anger and disgust relate to the judged appropriateness of sanctions, in a pre-registered analysis of data from a large-scale study in 56 societies. Across the world, we find that individuals who experience anger and disgust over a norm violation are more likely to endorse confrontation, ostracism and, to a smaller extent, gossip. Moreover, we find that the experience of anger is consistently the strongest predictor of judgments of confrontation, compared to other emotions. Although the link between state-based emotions and judgments may seem universal, its strength varies across countries. Aligned with theoretical predictions, this link is stronger in societies, and among individuals, that place higher value on individual autonomy. Thus, autonomy values may increase the role that emotions play in guiding judgments of social sanctions.

Theories of urban scaling have demonstrated remarkable predictive accuracy at aggregate levels. However, they have overlooked the stark inequalities that exist within cities. Human networking and productivity exhibit heavy-tailed distributions, with some individuals contributing disproportionately to city totals. Here we use micro-level data from Europe and the United States on interconnectivity, productivity and innovation in cities. We find that the tails of within-city distributions and their growth by city size account for 36–80% of previously reported scaling effects, and 56–87% of the variance in scaling between indicators of varying economic complexity. Providing explanatory depth to these findings, we identify a mechanism—city size-dependent cumulative advantage—that constitutes an important channel through which differences in the size of tails emerge. Our findings demonstrate that urban scaling is in large part a story about inequality in cities, implying that the causal processes underlying the heavier tails in larger cities must be considered in explanations of urban scaling. This result also shows that agglomeration effects benefit urban elites the most, with the majority of city dwellers partially excluded from the socio-economic benefits of growing cities.

The “transportability” of laboratory findings to other instances than the original implementation entails the robustness of rates of observed behaviors and estimated treatment effects to changes in the specific research setting and in the sample under study. In four studies based on incentivized games of fairness, trust, and reciprocity, we evaluate (1) the sensitivity of laboratory results to locally recruited student-subject pools, (2) the comparability of behavioral data collected online and, under varying anonymity conditions, in the laboratory, (3) the generalizability of student-based results to the broader population, and (4), with a replication at Amazon Mechanical Turk, the stability of laboratory results across research contexts. For the class of laboratory designs using interactive games as measurement instruments of prosocial behavior we find that rates of behavior and the exact behavioral differences between decision situations do not transport beyond specific implementations. Most clearly, data obtained from standard participant pools differ significantly from those from the broader population. This undermines the use of empirically motivated laboratory studies to establish descriptive parameters of human behavior. Directions of the behavioral differences between games, in contrast, are remarkably robust to changes in samples and settings. Moreover, we find no evidence for either anonymity effects nor mode effects potentially biasing laboratory measurement. These results underscore the capacity of laboratory experiments to establish generalizable causal effects in theory-driven designs.

Globalization makes cross-national encounters increasingly common. Hesitant cooperationacross national, ethnic, and cultural boundaries, however, undercuts the microlevel stabilizers of global integration and, most importantly, the willingness to share with and place trust in members of other social groups. In a 109-country online experiment, we convey information on interaction partners’ nationalities to indicate membership in a broader in- or out-group, cultural distance, and perceived material neediness—or status differences more generally—to 1,674 participants in incentivized games of generosity (dictator game) and trust (trust game). We find consistent evidence for in-group favoritism and—against this benchmark—demonstrate that individuals across the globe share more with but place less trust in interaction partners from poor countries and that cultural distance moderates this status effect.

We integrate insights from the social embeddedness perspective with research on immigrant entrepreneurship to theorize on how family resources influence exit from entrepreneurship among previously unemployed immigrant entrepreneurs. Results from a cohort study of immigrant entrepreneurs in Sweden reveal that family resources are important for immigrants to integrate economically into a country. We find that having family members in geographical proximity increases immigrant entrepreneurs’ likelihood of remaining in entrepreneurship. Further, family financial capital enhances immigrant entrepreneurs’ likelihood of remaining in entrepreneurship as well as their likelihood of exiting to paid employment. Although often neglected in immigrant entrepreneurship studies, resources accruing from spousal relationships with natives influence entrepreneurs’ exit behavior. We discuss contributions for research on entrepreneurial exit, entrepreneurs’ social embeddedness, and immigrant entrepreneurship.

The refugee crisis of 2015 became a major issue of both national and pan-European debate. Behavioral reactions among natives in the form of support for radical-right parties or leaving neighborhoods following influxes of non-Westerners are well documented, but a detailed account of how asylum seekers contribute to these dynamics remains elusive. In this paper, I study how asylum centers and refugees choosing their own residences prompt each of these two behavioral outcomes using register data for the whole of Sweden (2013–2018). The analyses show a divergence depending on the particular type of refugee exposure experienced and the specific behavior under analysis. Only increased radical-right support is observed following the establishment of a new asylum center, whereas greater native out-mobility is found following refugees self-selecting into native-based areas. 

Introduction: A crucial aspect of social norms pertains to determining which behaviors are considered appropriate. Here we consider everyday behaviors. Some everyday behaviors are rated as more appropriate than others, and ratings of the appropriateness of a given behavior may vary over time. The objective of this study is to elucidate the reasons behind variation in appropriateness ratings of everyday behaviors in the United States. Our theory focuses on how the evaluation of the appropriateness of a behavior is influenced by its potential for externalities and internalities, and how this influence may cause a change in norms over time.

Method: Employing a preregistered design, we asked American participants to rate 37 different everyday behaviors based on their appropriateness in a range of common situations, as well as their potential negative externalities (e.g., being loud, being aggressive, taking up space) and positive internalities (e.g., pleasurability). Changes over time were calculated as the difference between mean ratings obtained in this study and ratings of the same behavior in a similar study conducted 50 years ago.

Results: As expected, overall appropriateness ratings of everyday behaviors are associated both with their externalities and their internalities, so that the least appropriate behaviors tend to have considerable potential for negative externalities and little potential for positive internalities. Moreover, behaviors that have considerable potential for negative externalities are perceived as less appropriate now than 50 years ago.

Discussion: By describing how social norms for everyday behaviors depend on the externalities and internalities of behaviors, this study contributes to theories about the emergence and change of social norms.

Transparency is recognized as a crucial condition for accountability, good governance and democracy. As right to information (RTI) laws have spread, it has become crucial to ask whether ambitious legislative frameworks translate to de facto transparency. In this article, we test how well local governments in Sweden – a ‘most likely country’ for implementing RTI laws – comply with its comparatively ambitious Public Access to Information and Secrecy Act. As a side effect, we also gauge if New Public Management reforms, exemplified by increased public ownership of enterprises in local government, imply lessened compliance with RTI legislation. Requesting information from 462 randomly selected public administrations and municipally owned enterprises, counterintuitive findings were observed. Fewer than half of the organizations respected the RTI legislation, and no significant differences were found between the public administrations and publicly owned enterprises. The findings have methodological as well as empirical implications. They highlight the importance of not only studying legislative frameworks – as has frequently been done in previous work – but also of analyzing actual implementation of RTI frameworks in everyday situations. Additionally, the findings demonstrate that problems relating to openness can be observed in low corrupt, mature democracies with strong bureaucratic capacity. Lastly, and contrary to conventional wisdom, the findings indicate that publicly owned corporations do not necessarily imply an ‘accountability deficit’.

Knowledge-based theories of entrepreneurship infer transfer of knowledge from the effect of labor mobility on entrepreneurial entry. Yet, simple selection or situational mechanisms that do not imply knowledge transfer may influence entrepreneurial entry in similar ways. We argue that the extent to which such alternative mechanisms operate, labor mobility predicts entry but not subsequent performance for entrepreneurs. Analyses of matched employee–employer data from Sweden suggest that high rates of geographical and industry mobility increase individuals’ likelihood of entrepreneurial entry but have no effects on their entrepreneurial performance. This indicates that the relationship between labor mobility and entrepreneurial entry do not necessarily imply knowledge transfer.

Dominant explanations of segregation argue that patterns of spatial residential sorting are shaped by the aggregation of individual residential choices, guided by discrimination, differences in resources, and preference-based explanations of neighborhood ethnic composition. However, research on social networks indicates that social influence can serve as a driver of collective outcomes that result in social organization. I reconsider interactive behavior in line with the sociological literature on networks and social influence to advance the literature on how social contexts shape opportunities for interaction and how the social influence of social contexts may affect residential choices and subsequent segregation. To this end, I present three essays that address: 1) the macro implications of networked behavior in space, 2) the social influence effects of school peers during adulthood, and 3) how social contexts in neighborhoods, particularly in the form of local social infrastructure, modify the effects of social influence. In doing so, I demonstrate that network and institutional effects are empirically observable and show how they operate as mechanisms of segregation.

In the introductory chapter, I address the emerging literature on social structural sorting and detail how it can benefit from the adoption of an Analytical sociology perspective. In particular, I highlight the importance of considering interactions in space and social contexts and their importance to an understanding of persistent patterns of spatial residential segregation.

In Essay I, I provide an analytical account of how network features can shape residential segregation. I develop an Agent-based simulation similar to the seminal Schelling model but with the agents embedded in a social network structure. This allows me to experimentally manipulate network homophily, clustering, and degree to measure how each of these network features shapes segregation levels, patterns, and the stability of the social-spatial system. I show that depending on the combination of each of these features, network models can lead to even higher levels of residential sorting, driven by the interactive behavior of agents, than the seminal Schelling model. The results tie in with the classic sociological literature on social networks and highlight the importance of weak ties in tipping a social system into a segregated state.

Essay II examines the role of social influence among school peers in young adulthood. Scholarship has previously highlighted the role of kin in residential choices. However, there is less evidence about how non-kin ties can affect intra-urban residential choices. Drawing on the push-pull and housing-search model, our hypothesis posits that school peers serve as a potential pool of friends that influence one’s residential decisions. To unravel the dynamics of social influence and selection into neighborhoods, we utilize population register data and employ a cross-cohort design. Using conditional logistic regression models, we see that the influence of school peers from both the 9^th and 12^th grades affects residential choices during adulthood. Moreover, our analysis demonstrates that various life stages have distinct social foci, but that the persistent influence of school peers remains evident throughout.

Essay III examines how social contexts can modify social influence effects by providing an opportunity for interaction. We combine population register data with OpenStreetMap data to map the amenity landscape in Stockholm and test whether neighborhood-level infrastructure mitigates tendencies towards white flight behavior. We employ coarsened exact matching to address selection bias into neighborhoods and estimate weighted linear probability regressions to assess the probability of majority group members’ out-mobility. We find that local social amenities located on the city block can indeed reduce tendencies towards white flight behavior. However, with increasing amenity density in the neighborhoods, majority group members become more likely to engage in white flight. We conclude that amenity density allows neighborhood residents to sort into different establishments, which does not promote intergroup contact. However, if amenities are local, which presumably facilitates frequent contact with neighbors, opportunities for interaction can reduce intolerant behavior, highlighting how social contexts are important mechanisms of segregation.

The advantages of groups over individuals in complex decision-making have long interested scientists across disciplinary divisions. Averaging over a collection of individual judgments proves a reliable strategy for aggregating information, particularly in diverse groups in which statistically independent beliefs fall on both sides of the truth and contradictory biases are cancelled out. Social influence, some have said, narrows variation in individual opinions and undermines this wisdom-of-crowds effect in continuous estimation tasks. Researchers, however, neglected to study social-influence effects on voting in discrete choice tasks. Using agent-based simulation, we show that under voting — the most widespread social decision rule — social influence contributes to information aggregation and thus strengthens collective judgment. Adding to our knowledge about complex systems comprised of adaptive agents, this finding has important ramifications for the design of collective decision-making in both public administration and private firms.

Word embeddings have demonstrated strong performance on NLP tasks. However, lack of interpretability and the unsupervised nature of word embeddings have limited their use within computational social science and digital humanities. We propose the use of informative priors to create interpretable and domain-informed dimensions for probabilistic word embeddings. Experimental results show that sensible priors can capture latent semantic concepts better than or on-par with the current state of the art, while retaining the simplicity and generalizability of using priors.

There is an increasing wealth of models trying to explain the evolution of group discrimination and an ingroup bias. This paper sets out to systematically investigate the most fundamental assumption in these models: in what kind of situations do the interactions take place? What strategic structures – games – support the evolution of an ingroup bias? More specifically, the aim here is to find the prerequisites for when a bias also with respect to minimal groups – arbitrarily defined groups void of group-specific qualities – is selected for, and which cannot be ascribed to kin selection.

Through analyses and simulations of minimal models of two-person games, this paper indicates that only some games are conducive to the evolution of ingroup favouritism. In particular, this class does not contain the prisoners' dilemma, but it does contain anti-co-ordination and co-ordination games. Contrasting to the prisoners' dilemma, these are games where it is not a matter of whether to behave altruistically, but rather one of predicting what the other person will be doing, and where I would benefit from you knowing my intentions.

In anti-co-ordination games, on average, not only will agents discriminate between groups, but also in such a way that their choices maximise the sum of the available payoffs towards the ingroup more often than towards the outgroup. And in co-ordination games, even if agents do manage to co-ordinate with the whole population, they are more likely to co-ordinate on the socially optimal equilibrium within their group. Simulations show that this occurs most often in games where there is a component of risk-taking, and thus trust, involved. A typical such game is the stag hunt or assurance game.

Various theories have been proposed regarding the origin of creole languages. Describing a process where only the end result is documented involves several methodological difficulties. In this paper we try to address some of the issues by using a novel mathematical model together with detailed empirical data on the origin and structure of Mauritian Creole. Our main focus is on whether Mauritian Creole may have originated only from a mutual desire to communicate, without a target language or prestige bias. Our conclusions are affirmative. With a confirmation bias towards learning from successful communication, the model predicts Mauritian Creole better than any of the input languages, including the lexifier French, thus providing a compelling and specific hypothetical model of how creoles emerge. The results also show that it may be possible for a creole to develop quickly after first contact, and that it was created mostly from material found in the input languages, but without inheriting their morphology.

Analytical sociology is beginning to embrace a digital revolution in the collection and analysis of social data and is increasingly drawing on tools from computational social science (CSS) to pursue its goals of mechanism-based explanation of aggregate outcomes. In this chapter, we highlight the ways in which analytical sociologists are using CSS tools to further social research. Using agent-based modeling, large-scale online experiments, digital trace data, and natural language processing, analytical sociologists are identifying how large-scale properties of social systems emerge from the complex interactions of networked actors at lower scales. At the same time, we provide a perspective on how CSS techniques can be successfully deployed in social research, including ways in which they can be productively combined. Computational tools, when applied using a theory-grounded approach, offer sociologists a chance to transcend the limitations of the dominant survey-research paradigm and finally address “big” sociological questions about, for example, the nature of culture, the emergence of inequality, and the dynamics of segregation. We also discuss how computational social scientists can take cues from analytical sociology to further hone their own research and methods in the service of theoretically grounded, mechanism-based explanations, moving beyond theoretically thin descriptions or predictions of micro- and macro-level outcomes.

Some regions of the United Kingdom present more fertile grounds for consecutive incarnations of extreme right parties than others. In a study by Goodwin, Ford and Cutts the authors found evidence of the legacy effect, where an earlier cycle of activism by the National Front (NF), an extreme right political party active in the 1970s, emerged as a strong and significant predictor of membership in the British National Party (BNP) three decades later. While their study speaks to the supply-side arguments for extreme right success (organizational continuity and local cultural traditions in particular), here we examine whether a similar legacy effect can be observed with respect to demand for extreme right politics. As we are going to show there is some overlap between the share of votes cast for the NF and the BNP, yet there are a number of constituencies that do not adhere to this pattern. We conclude that while the supply-side legacy effect is not ruled out, the legacy effect hypothesis does not find support for demand-side explanation of extreme right support.

This paper discusses social mechanisms of discrimination and reviews existing field experimental designs for their identication. We first explicate two social mechanisms proposed in the literature, animus-driven and statistical discrimination, to explain differential treatment based on ascriptive characteristics. We then present common approaches to study discrimination based on observational data and laboratory experiments, discuss their strengths and weaknesses, and elaborate why unobtrusive field experiments are a promising complement. However, apart from specific methodological challenges, well-established experimental designs fail to identify the mechanisms of discrimination. Consequently, we introduce a rapidly growing strand of research which actively intervenes in market activities varying costs and information for potential perpetrators to identify causal pathways of discrimination. We end with a summary of lessons learned and a discussion of challenges that lie ahead.

Entrepreneurial action is embedded within a variety of complex social structures, not all of which can be as easily defined or measured as macro-institutional or micro-individual characteristics, but collectively hold rich insights into the actual causal mechanisms influencing action. To address this problem, we call upon researchers to broaden their levels of analysis and direct their focus to mesolevel structures. Although meso-level social structures are widely studied independently, these intermediate levels are seldom integrated into existing multi-level models. We argue that meso-level structures offer untapped riches for enhancing multi-level entrepreneurial mechanisms and discuss how social groups, associations, and other collectives operating at a meso-level can play a more distinct integrative role in between the two ends of the institutional spectrum. To provide practical guidance for pursuing such investigations, we adapt Coleman’s Bathtub model to form a robust framework that integrates micro, meso, and macro levels of analysis. Our framework helps alleviate the shortcomings produced by an overdependence on either solely macro- or micro-level entrepreneurial mechanisms and brings the hidden intermediate level into plain sight.

The study of income inequality has a rich history within economics and various social sciences. More recently, a growing body of literature has examined intergenerational income mobility to understand not only equality of opportunities but also whether the labor market allocation successfully utilizes the potential abilities from all social strata. This dissertation explores the intricate relationship between income inequality and intergenerational mobility through three distinct research articles.

If we envision the income distribution as a ladder, income inequality can be likened to the relative distance between the ladder’s rungs, where greater inequality corresponds to a more stretched-out ladder. Income mobility, on the other hand, is a much more multifaceted concept. The most common way of measuring it is relative mobility, which tries to quantify the mobility between the rungs of the ladder, where an upward jump for one born poor necessarily implies a downward shift for one born richer.

Article 1 studies how relative mobility is affected by income inequality across regions within Sweden. If there are substantial income differences across regions within countries that persist across generations, this will contribute to a more stretched-out ladder, potentially making mobility more difficult. The study demonstrates that these regional income disparities persist across generations, resulting in decreased income mobility. The article then proceeds to examine whether migration patterns between richer and poorer regions mitigate or exacerbate this effect.

In contrast to relative mobility, absolute mobility measures if children end up being better off in the standard of living compared to their parents, regardless of whether they manage to climb to a higher rung on the ladder compared to their parents. Article 2 delves into examining the trend in absolute income mobility for Sweden, measured as the percentage of children earning more than their parents. The novel decomposition method reveals that Sweden has a high level of absolute mobility mainly due to the low level of income inequality.

Article 3 explores the potential of public education to mitigate inequities by examining the causal effects of a 1989 Swedish teacher strike that caused school closures. The article reveals that the strike had both negative short-run effects, measured as student results, and long-run effects, measured as earnings, and the effects were larger for individuals from low-income backgrounds.

In summary, this dissertation provides both empirical and methodological contributions to the intricate relationship between inequality and mobility.

We use full-population data to study trends in intergenerational absolute income mobility, measured as the ratio of children earning more than their parents, for 11 Swedish cohorts born 1972–1983. Absolute mobility during this period increases from 72% to 84% for men and from 76% to 86% for women—higher figures than in most other countries studied. To explain these results, we outline a novel decomposition strategy that accounts for cohort variation in parent-generation income inequality. All else equal, if income inequality is higher in the parent generation, more economic growth is required to achieve any given level of absolute mobility. We discuss implications for comparative research in intergenerational income mobility.

In their authoritative literature review, Breen and Jonsson (2005) claim that ‘one of the most significant trends in the study of inequalities in educational attainment in the past decade has been the resurgence of rational-choice models focusing on educational decision making’. The starting point of the present contribution is that these models have largely ignored the explanatory relevance of social interactions. To remedy this shortcoming, this paper introduces a micro-founded formal model of the macro-level structure of educational inequality, which frames educational choices as the result of both subjective ability/benefit evaluations and peer-group pressures. As acknowledged by Durlauf (2002, 2006) and Akerlof (1997), however, while the social psychology and ethnographic literature provides abundant empirical evidence of the explanatory relevance of social interactions, statistical evidence on their causal effect is still flawed by identification and selection bias problems. To assess the relative explanatory contribution of the micro-level and network-based mechanisms hypothesised, the paper opts for agent-based computational simulations. In particular, the technique is used to deduce the macro-level consequences of each mechanism (sequentially introduced) and to test these consequences against French aggregate individual-level survey data. The paper's main result is that ability and subjective perceptions of education benefits, no matter how intensely differentiated across agent groups, are not sufficient on their own to generate the actual stratification of educational choices across educational backgrounds existing in France at the beginning of the twenty-first century. By computational counterfactual manipulations, the paper proves that network-based interdependencies among educational choices are instead necessary, and that they contribute, over and above the differentiation of ability and of benefit perceptions, to the genesis of educational stratification by amplifying the segregation of the educational choices that agents make on the basis of purely private ability/benefit calculations

Studies of social mobility typically focus on the associations between the socioeconomic characteristics of individuals and families in one generation and those same characteristics for the next generation. Yet the life chances of individuals may be affected by a wider network of kin than just the nuclear family, including grandparents, aunts and uncles, siblings, and even more remote kin. In planning new studies of intergenerational social mobility, researchers should consider the ways that more remote kin may affect socioeconomic success and hardship and design data collection strategies for collecting data on wider kin networks. Administrative record linkage and survey research have complementary advantages for identifying kin networks. Successful implementation of these approaches holds the promise of a much richer set of studies of intergenerational social mobility than most researchers have attempted thus far.

"To anyone familiar with the French political scene, the 2017 election season felt atypical. Normally, during these moments of intense attention on politics, the main issues often revolve around broader issues. Security, taxation, immigration, or more recently the environment, are more likely to capture the public's attention than the careers of political representatives. But not in 2017. That year the attention was focused on the biography of the political personnel, and the term "les professionnel de la politique" [professional politicians] became a ubiquitous insult in public debate. But neither in France nor abroad was this attention to the political elite fully unprecedented. Rather, it marked the latest revival of an insult that is as old as the compensation of politicians for their work. The criticism of professional politicians had been widely revived over the previous decade. An apparently trivial example provides a good illustration of this. In blog post from September 2014, Michèle Delaunay, a former Socialist MP, lamented the arrival of a new generation into politics. According to her, those moving into national politics in the 2010s shared one trait: the vast majority of them had had no professional experience outside this milieu. Although she did not use the term "professional" or "career politicians", as such, her target was clear. "They graduate from Sciences Po [the school of the political elite], take an administrative exam, or not, they look around ... Then they get a position as a staffer or a local government job. The luckiest, or cleverest of them end up as a top aide to a cabinet member. In this ever so slightly limited world, they catch the bug." Describing the stages in a well-oiled career, Delaunay, a former oncologist, observed at the end of her career that her youngest colleagues had less and less experience outside politics. The image she used is telling. She wrote that "they go into the tunnel early and never come out." According to her, the consequences are immense. Once they set out on this path, these ambitious young people "lose touch with reality and the sense of the common good." As they get older, they behave as if they are "beyond even the most basic rules""--Provided by publisher.

How does the ideological segregation of online networks impact the spread of misinformation? Paststudies have found that homophily generally increases diffusion, suggesting that partisan news,whether true or false, will spread farther in ideologically segregated networks. We argue that networksegregation disproportionately aids messages that are otherwise too implausible to diffuse, thusfavoring false over true news. To test this argument, we seeded true and false informational messagesin experimental networks in which subjects were either ideologically integrated or segregated,yielding 512 controlled propagation histories in 16 independent information systems. Experimentalresults reveal that the fraction of false information circulating was systematically greater inideologically segregated networks. Agent-based models show robustness of this finding acrossdifferent network topologies and sizes. We conclude that partisan sorting undermines the veracity ofinformation circulating on the Internet by increasing exposure to content that would otherwise notmanage to diffuse.

By introducing the concept of high-reach AI, this paper focuses on AI systems whose widespread use may generate significant risks for both individuals and societies. While some of those risks have been recognised under the AI Act, we analyse the rules laid down by the Digital Services Act (DSA) for recommender systems used by dominant social media platforms as a prominent example of high-reach AI. Specifically, we examine transparency provisions aimed at addressing adverse effects of these AI technologies employed by social media very large online platforms (VLOPs). Drawing from AI transparency literature, we analyse DSA transparency measures through the conceptual lens of horizontal and vertical transparency. Our analysis indicates that while the DSA incorporates transparency provisions in both dimensions, the most progressive amendments emerge within the vertical transparency, for instance, by the introduction of the systemic risk assessment mechanism. However, we argue that the true impact of the new transparency provisions extends beyond their mere existence, emphasising the critical role of oversight entities in implementation and application of the DSA. Overall, this study highlights the paramount importance of vertical transparency in providing a comprehensive understanding of the aggregated risks associated with high-reach AI technologies, exemplified by social media recommender systems.