We present the Random Exchange model, an extension of the bilateral exchange model of collective decision-making of Stokman and Van Oosten. Compared to more elementary models, the Random Exchange model generates predictions of the process leading to the outcome and enhances understanding of deadlock or difficulties in the negotiation process. After explaining its logic, the Random Exchange model is applied to collective decision-making in the international setting of two climate agreements, chaired by the European Union; the 2009 Climate Conference of Parties (COP) in Copenhagen, and the 2015 COP in Paris. The applications show how Random Exchange model not only may be used to predict collective decision-making outcomes but also deadlock when powerful actors attach high relative saliences to at least two issues on which they have opposite positions.

How individuals value their own and others' outcomes is conceptualized as their Social Value Orientation (SVO). Research demonstrates that SVO is a valid predictor of cooperative behavior across various empirical settings. However, once individuals interact repeatedly, the relative strength and stability of the SVO-behavior link are less clear cut. We postulate that learning mechanisms have a bearing on cooperative behavior and potentially override the influence of SVO. In an experiment with a Step-Level Public Goods design with impact asymmetry (N = 120), participants were randomly assigned to groups of five and interacted for six rounds. SVO was measured with the 9-item Triple-Dominance Measure. Using a multi-level Bayesian approach, we corroborate that SVO is predictive of behavior at the onset of interaction. Yet, after the first interaction, the relationship between SVO and behavior virtually disappears.

We propose a model of cumulative advantage (CA) as an unintended consequence of the choices of a population of individuals. Each individual searches for a high quality object from a set comprising high and low quality objects. Individuals rationally learn from their own experience with objects (reinforcement learning) and from the observation of others’ choices (social learning). We show that CA emerges inexorably as individuals rely more on social learning and as they learn from more rather than fewer others. Our theory argues that CA has social dilemma features: the benefits of CA could be enjoyed with modest drawbacks provided individuals would practice restraint in their social learning. However, when practiced by everyone such restraint goes against the individual’s self-interest.

A prevalent assumption in metaethics is that people believe in moral objectivity. If this assumption were true then people should believe in the possibility of objective moral progress, objective moral knowledge, and objective moral error. We developed surveys to investigate whether these predictions hold. Our results suggest that, neither abstractly nor concretely, people dominantly believe in the possibility of objective moral progress, knowledge and error. They attribute less objectivity to these phenomena than in the case of science and no more, or only slightly more, than in the cases of social conventions and personal preferences. This finding was obtained for a regular sample as well as for a sample of people who are particularly likely to be reflective and informed (philosophers and philosophy students). Our paper hence contributes to recent empirical challenges to the thesis that people believe in moral objectivity.

This perspective paper argues how a social network approach can contribute to creating a more comprehensive picture of how individual and community characteristics influence participation in community energy initiatives (CEIs). We argue how social network theory and methods for social network analysis can be utilized to better understand participation. Further, we show how this can potentially aid the implementation of interventions aimed at attracting more participants with more diverse socio-demographic backgrounds. Importantly, we argue that the structure of community social networks connecting (potential) participants could importantly influence whether and how individual and community properties affect CEI participation. Our aim is conveying the social network approach to the field of community energy researchers and stakeholders who might not be familiar with it. We discuss empirical evidence on the effect of network characteristics on CEI participation and the connection between research on CEIs and adjacent fields as a foundation for our claims. We also illustrate how a social network approach might help to overcome biased participation and low participation numbers, by providing social scientists with a tool to give empirically grounded advice to CEIs. We conclude by looking at avenues for future research and discuss how the context of CEIs might yield new theoretical insights and hypotheses.

The excellence and integrity of Rationality and Society depends on the dedication and expertise of volunteer reviewers who evaluate submissions for their contribution to the discipline, soundness of research, writing clarity, and general interest. With apologies to any inadvertently omitted reviewers, the editors of Rationality and Society extend sincere thanks to the following reviewers for providing highly valuable comments on papers submitted in 2020 and 2021:

Decades of research show that ( i ) social value orientation (SVO) is related to important behavioral outcomes such as cooperation and charitable giving, and ( ii ) individuals differ in terms of SVO. A prominent scale to measure SVO is the social value orientation slider measure (SVOSM). The central premise is that SVOSM captures a stable trait. But it is unknown how reliable the SVOSM is over repeated measurements more than one week apart. To fill this knowledge gap, we followed a sample of N = 495 over 6 months with monthly SVO measurements. We find that continuous SVO scores are similarly distributed (Anderson-Darling k-sample p = 0.57) and highly correlated ( r ≥ 0.66) across waves. The intra-class correlation coefficient of 0.78 attests to a high test-retest reliability. Using multilevel modeling and multiple visualizations, we furthermore find that one’s prior SVO score is highly indicative of SVO in future waves, suggesting that the slider measure consistently captures one’s SVO. Our analyses validate the slider measure as a reliable SVO scale.

Meritocratic matching solves the problem of cooperation by ensuring that only prosocial agents group together while excluding proselfs who are less inclined to cooperate. However, matching is less effective when estimations of individual merit rely on group-level outcomes. Prosocials in uncooperative groups are unable to change the nature of the group and are themselves forced to defect to avoid exploitation. They are then indistinguishable from proselfs, preventing them from accessing cooperative groups. We investigate informal social networks as a potential solution. Interactions in dyadic network relations provide signals of individual cooperativeness which are easier to interpret. Network relations can thus help prosocials to escape from uncooperative groups. To test our intuitions, we develop an ABM modeling cooperative behavior based on a stochastic learning model with adaptive thresholds. We investigate both randomly and homophilously formed networks. We find that homophilous networks create conditions under which meritocratic matching can function as intended. Simulation experiments identify two underlying reasons. First, dyadic network interactions in homophilous networks differentiate more between prosocials and proselfs. Second, homophilous networks create groups of prosocial agents who are aware of each other's behavior. The stronger this prosociality segregation is, the more easily prosocials cooperate in the group context. Further analyses also highlight a downside of homophilous networks. When prosocials successfully escape from uncooperative groups, noncooperatives have fewer encounters with prosocials, diminishing their chances to learn to cooperate through those encounters.

Community energy initiatives are set up by volunteers in local communities to promote sustainable energy behaviors and help to facilitate a sustainable energy transition. A key question is what motivates people to be involved in such initiatives. We propose that next to a stronger personal motivation for sustainable energy, people’s perception that their community is motivated to engage in sustainable energy and their involvement in the community (i.e., community identification and interpersonal contact) may affect their initiative involvement. We tested this proposition with a questionnaire study among inhabitants of seven local communities (N = 439). Results suggested that community factors are uniquely related to initiative involvement (willingness to actively participate and attendance of an initiative meeting) next to personal sustainable energy motivations. In particular, stronger community identification and more interpersonal contact with other community members increased the likelihood that people become involved in a community initiative, but the perception of the sustainable energy motivation of one’s community was not uniquely related to initiative involvement. We discuss theoretical and practical implications of these findings.

This study investigates the role of social networks in influencing individuals' decision whether to participate in a community energy initiative (CEI), by incorporating different types of social contact between community members and CEI initiators. Engagement of community members is crucial for the success of a CEI and thus a key question is how the initiators can reach community members and stimulate involvement. By analyzing the community's social network we investigate how the structure of social ties between community members and initiators influences participation. We take both existence and number of strong and weak direct personal ties into account. In addition, we investigate the role of extended ties community members have to initiators, operationalized via indirect links through co-memberships of local associations. Data were obtained from eight communities in the Netherlands where a CEI was recently initiated (N = 467 respondents). Our results demonstrate that community members' willingness to participate in a CEI is positively associated with direct ties to the initiators, both weak and strong, but there is no association with extended ties to initiators. Possible strategies of how initiators might best utilize their social ties are discussed.

We develop a model of strategic network formation of collaborations to analyze the consequences of an understudied but consequential form of heterogeneity: differences between actors in the form of their production functions. We also address how this interacts with resource heterogeneity, as a way to measure the impact actors have as potential partners on a collaborative project. Some actors (e.g., start-up firms) may exhibit increasing returns to their investment into collaboration projects, while others (e.g., established firms) may face decreasing returns. Our model provides insights into how actor heterogeneity can help explain well-observed collaboration patterns. We show that if there is a direct relation between increasing returns and resources, start-ups exclude mature firms and networks become segregated by types of production function, portraying DOMINANT GROUP architectures. On the other hand, if there is an inverse relation between increasing returns and resources, networks portray CORE-PERIPHERY architectures, where the mature firms form a core and start-ups with low-resources link to them.

The Slider Measure of social value orientation (SVO) was introduced as an improvement from existing measures. We conduct an independent assessment of its suitability compared with the Ring Measure and the Triple Dominance Measure. Using a student sample, we assess the measures' test-retest reliability (N = 88; using a longer time interval than previous studies) and sensitivity to random responses. Analyses pertaining to convergent validity, criterion validity, and the advantages of a continuous over a discrete measure are presented in the online appendix. Compared with alternatives, the Slider Measure has the highest test-retest reliability. However, it classifies random responses in an unbalanced way, assigning the vast majority of random responses to cooperative and individualistic, rather than altruistic and competitive, orientations. For all three measures, we propose improved ways of weeding out inconsistent responses.

: When examining a social phenomenon, theoretical and empirical sociologists require a model. Although models are by definition simplified representations of theories of reality, sociologists typically argue that the micro-level model of individual behavior should be simplified, but not the model of the macro-level system (including macro-micro and micro-macro links) including the social interactions. Using the example of research on exchange we theoretically and empirically demonstrate the possibly disastrous consequences of overly simplifying the model of the macro-level system. We show that by oversimplification, the mainstream model of exchange (so-called split pool exchange) precludes explaining the macro-level phenomenon. Consequently, we question the ecological validity of exchange research for real-life exchanges. We conclude by listing advantages of a more complex and realistic macro-level model of exchange (that is, pure exchange) for research in the social sciences. abstract away ’ crucial aspects of the phenomenon to be explained; bargaining behavior in (bilateral) exchange. Such bargaining behavior in the real world very often involves the transfer of actual goods, that is, is best conceptualized as pure exchange. The results of Dijkstra and Van Assen (2008) show that such bargaining behavior (i) is much less accurately predicted by existing bargaining theories than suggested by split pool exchange studies, (ii) seems much less predictable (much more variable) than suggested by split pool exchange, in the first place, and (iii) much more frequently leads to Pareto inefficient outcomes than suggested by split pool exchange studies. Note how the second implication (related to the higher variability of outcomes in pure exchange) points to the need of theoretically including covariates (such as bargaining skills, or mental models of the bargaining situation) that have hitherto been neglected in many bargaining and exchange theories. This drives home the point that accurate macro-models are crucial for fruitful theory development.

Settling for less: a deliberate political choice or a lack of information? In a well-functioning democracy voters should elect parties and representatives with whom they agree on policy issues. The current paper investigates the extent to which Dutch voters in the 2017 parliamentary election had accurate information about parties’ policy positions. We elicit the extent to which voters think they vote for parties with whom they maximally agree (subjective congruence) and the extent to which this is actually true (objective congruence). Results show voters in our sample to have accurate information about approximately half of the policy positions of a random large party. Only 21.5 percent voted for a party with whom they were maximally objectively congruent. Objective congruence does not increase with information accuracy. Voters appear to consciously accept losses in terms of subjective congruence, as only 34.7 percent votes for a party with whom they think to be maximally congruent. These results are compatible with the interpretation of voters first choosing a party, and then (to some degree) adapting their personal policy positions to those of the chosen party.

In his contribution Policy Networks: History to the Encyclopedia of Social Network Analysis and Mining (2017), Stokman distinguishes three fundamental processes of collective decision making (persuasion, logrolling, and enforcement), and specifies conditions under which each type of process is dominant. The Python software tool Decide is a userfriendly, publicly available tool for generating, documenting and analyzing data of two fundamental collective decision making processes: persuasion and logrolling. The tutorial not only provides instructions for the use of the Python tool, but also an introduction to collective decision making theory and research and its relation with different types of social networks. Tool and examples will be illustrated using important international decision making processes, like the Copenhagen and Paris Climate Negotiations and negotiation processes in the European Union. Outline of the tutorial • Introduction to the three fundamental processes of collective decision making: persuasion, logrolling (exchange) and enforcement based on the Policy Networks: History article. • Introduction of the Python-tool Decide • Illustration of the tool and model outcomes on the basis of the data collected to predict the outcomes of the Copenhagen Climate Conference • Introduction to the stochastic extension of the earlier model • Downloading of the program on the notebooks of the participants • Exercises with Copenhagen and Paris Climate Conferences and European Union Decides datasets • Discussion of output Recommended reading: http://stokman.org/artikel/17%20Policy%20Networks_%20History%20-%20Springer.pdf

Analytical sociology explains macro-level outcomes by referring to micro-level behaviors, and its hypotheses thus take macro-level entities (e.g. groups) as their units of analysis. The statistical analysis of these macro-level units is problematic, since macro units are often few in number, leading to low statistical power. Additionally, micro-level processes take place within macro units, but tests on macro-level units cannot adequately deal with these processes. Consequently, much analytical sociology focuses on testing micro-level predictions. We propose a better alternative; a method to test macro hypotheses on micro data, using randomization tests. The advantages of our method are (i) increased statistical power, (ii) possibilities to control for micro covariates, and (iii) the possibility to test macro hypotheses without macro units. We provide a heuristic description of our method and illustrate it with data from a published study. Data and R-scripts for this paper are available in the Open Science Framework (https://osf.io/scfx3/).

In Step-Level Public Good (SPG) situations, groups of individuals can produce a public good if a sufficient number of them contribute. In SPG situations it is thus only rational for any group member to contribute if according to the beliefs of that group member her contribution is essential to the production of the public good. An individual's estimate of the impact of their contribution on the likelihood of public good production is known as their efficacy. The classic efficacy – cooperation hypothesis holds that individuals will be more likely to contribute if they estimate their contributions to be more necessary. Based on a game theoretical analysis of the SPG game, we contribute to the literature by identifying two distinct components of efficacy, viz. material efficacy and contextual efficacy. The former is based on objective characteristics of group members (such as resources, power, or skill) and the latter on beliefs about the material efficacy of other group members and expectations concerning their behavior. We present evidence from three experimental studies, showing how information on the distribution of material efficacy in the group can break the monotone material efficacy – cooperation relation. In addition, contrary to what one would expect based on both the efficacy – cooperation hypothesis and game theory, our results show that the effects of material efficacy are not mediated by contextual efficacy, both forms of efficacy having significant effects on behavior.

Objective: To examine the impact of perceived limitations, stigma and sense of coherence on quality of life in multiple sclerosis patients. Design: Cross-sectional survey. Setting: Department of Neurology, University Medical Center Groningen, the Netherlands. Subjects: Multiple sclerosis patients. Main measures: World Health Organization Quality of Life - abbreviated version, Stigma Scale for Chronic Illness, Sense of Coherence Scale, background and disease-related questions. Results: In total, 185 patients (61% response rate) participated in the study with moderate to severe limitations. Stigma was highly prevalent but low in severity. Patients with a higher sense of coherence experienced a lower level of limitations (B = -0.063, P < 0.01) and less stigma (enacted stigma B = -0.030, P < 0.01; self-stigma B = -0.037, P < 0.01). Patients with a higher level of limitations experienced more stigma (enacted stigma B = 0.044, P < 0.05; self-stigma B = 0.063, P < 0.01). Patients with a higher sense of coherence experienced better quality of life (physical health B = 0.059, P < 0.01; psychological health B = 0.062, P < 0.01; social relationships B = 0.052, P < 0.01; environmental aspects B = 0.030, P < 0.01). Patients with a higher level of limitations experienced poorer quality of life (physical health B= -0.364, P < 0.01; psychological health B = -0.089, P< 0.05) and patients with more stigma also experienced poorer quality of life (self-stigma: physical health B = -0.073, P < 0.01; psychological health B = -0.089, P < 0.01; social relationships B = -0.124, P < 0.01; environmental aspects B = -0.052, P < 0.01, and enacted stigma: physical health B = -0.085, P < 0.10). Conclusion: Patients with less perceived limitations and stigma and a higher level of sense of coherence experienced better quality of life. Patients with a higher sense of coherence experienced a lower level of limitations and less stigma.

Peer sanctioning institutions are powerful solutions to the freerider problem in collective action. However, counter-punishment may deter sanctioning, undermining the institution. Peer-reward can be similarly vulnerable, because peers may exchange rewards for rewards (“counter-reward”) rather than enforce contributions to the collective good. Based on social exchange arguments, we hypothesize that peerreward is vulnerable in a repeated game where players are fully informed about who rewarded them in the past. Social preference arguments suggest that peer-punishment is robust under the same conditions. This contrast was tested in an experiment in which counter-sanctioning was precluded due to anonymity of enforcers in one treatment and allowed in another treatment by non-anonymity of enforcers. This was done both for a reward and for a punishment institution. In line with the exchange argument, non-anonymity boosted reward-reward exchanges. Punishment was only somewhat reduced when enforcers were not anonymous. In contrast with previous experiments, we found no effects of counter-sanctioning on contributions. Thus, nonanonymity did not undermine the effectiveness of the peer sanctioning institutions in our experiments, neither for reward nor for punishment. Our results suggest that previous claims about the vulnerability of peer-punishment to counter-punishment may not generalize to non-anonymous repeated interactions.