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The growing polarization of our societies and economies has been extensively studied in various disciplines and is subject to public controversy. Yet, measuring polarization is hampered by the discrepancy between how polarization is conceptualized and measured. For instance, the notion of group, especially groups that are identified based on similarities between individuals, is key to conceptualizing polarization but is usually neglected when measuring polarization. To address the issue, this paper presents a new polarization measurement based on a grouping method called “Equal Size Binary Grouping” (ESBG) for both uni- and multi-dimensional discrete data, which satisfies a range of desired properties. Inspired by techniques of clustering, ESBG divides the population into two groups of equal sizes based on similarities between individuals, while overcoming certain theoretical and practical problems afflicting other grouping methods, such as discontinuity and contradiction of reasoning. Our new polarization measurement and the grouping method are illustrated by applying them to a two-dimensional synthetic data set. By means of a so-called “squeezing-and-moving” framework, we show that our measurement is closely related to bipolarization and could help stimulate further empirical research.

Agent-Based Modeling (ABM) is a computational method used to examine social outcomes emerging from interaction between heterogeneous agents by computer simulation. It can be used to understand the effect of initial conditions on complex outcomes by exploring fine-grained (multiple-scale, spatial/temporal) observations on the aggregate consequences of agent interaction. By performing in silico experimental tests on policy interventions where ex ante predictions of outcomes are difficult, it can also reduce costs, explore assumptions and boundary conditions, as well as overcome ethical constraints associated with the use of randomized controlled trials in behavioral policy. Here, we introduce the essential elements of ABM and present two simple examples where we assess the hypothetical impact of certain policy interventions while considering different possible reactions of individuals involved in the context. Although highly abstract, these examples suggest that ABM can be either a complement or an alternative to behavioral policy methods, especially when understanding social processes and exploring direct and indirect effects of interventions are important. Prospects and critical problems of these in silico policy experiments are then discussed.

Improving the methodological rigour and the quality of data analysis in manuscripts submitted to journals is key to ensure the validity of scientific claims. However, there is scant knowledge of how manuscripts change throughout the review process in academic journals. Here, we examined 27 467 manuscripts submitted to four journals from the Royal Society (2006–2017) and analysed the effect of peer review on the amount of statistical content of manuscripts, i.e. one of the most important aspects to assess the methodological rigour of manuscripts. We found that manuscripts with both initial low or high levels of statistical content increased their statistical content during peer review. The availability of guidelines on statistics in the review forms of journals was associated with an initial similarity of statistical content of manuscripts but did not have any relevant implications on manuscript change during peer review. We found that when reports were more concentrated on statistical content, there was a higher probability that these manuscripts were eventually rejected by editors.

Manuscripts have a complex development process with multiple influencing factors. Reconstructing this process is difficult without large-scale, comparable data on different versions of manuscripts. Preprints are increasingly available and may provide access to the earliest manuscript versions. Here, we matched 6,024 preprint-publication pairs across multiple fields and examined changes in their reference lists between the manuscript versions as one aspect of manuscripts' development. We also qualitatively analysed the context of references to investigate the potential reasons for changes. We found that 90 percent of references were unchanged between versions and 8 percent were newly added. We found that manuscripts in the natural and medical sciences undergo more extensive reframing of the literature while changes in engineering mostly focused on methodological details. Our qualitative analysis suggests that peer review increases the methodological soundness of scientific claims, improves the communication of findings, and ensures appropriate credit for previous research., Comment: Manuscripts; Peer Review; Preprints; Reference Lists Changes; Publications

Examining coauthorship networks is key to study scientific collaboration patterns and structural characteristics of scientific communities. Here, we studied coauthorship networks of sociologists in Italy, using temporal and multi-level quantitative analysis. By looking at publications indexed in Scopus, we detected research communities among Italian sociologists. We found that Italian sociologists are fractured in many disconnected groups. The giant connected component of the Italian sociology could be split into five main groups with a mixture of three main disciplinary topics: sociology of culture and communication (present in two groups), economic sociology (present in three groups) and general sociology (present in three groups). By applying an exponential random graph model, we found that collaboration ties are mainly driven by the research interests of these groups. Other factors, such as preferential attachment, gender and affiliation homophily are also important, but the effect of gender fades away once other factors are controlled for. Our research shows the advantages of multi-level and temporal network analysis in revealing the complexity of scientific collaboration patterns.

This paper examines age discrimination in hiring against elderly workers in Italy. By means of a role-game laboratory experiment, we estimated the effect of age and certain important mediating factors, such as job experience and training, on hiring decisions, by considering also social influence and stereotypes. Our findings indicate that age discrimination against older people does exist even when candidates have comparable characteristics. Results suggest that although the Italian population has one of the highest life expectancies worldwide, health stereotypes are the most important determinant of this effect. However, we found that experience and up-to-date training by elderly workers could counterbalance this negative effect.

No formal investigations have been conducted into the efficacy or potential influence of reviewer recommendations on editorial decisions, and the impact of this on the expectations and behaviour of authors, reviewers and journal editors. This article addresses key questions about this critical aspect of the peer review submission process. We suggest several future steps which could be taken towards improving the review process and make it more transparent, better understood, and fairer for all parties.

The COVID-19 pandemic is causing a dramatic loss of lives worldwide, challenging the sustainability of our health care systems, threatening economic meltdown, and putting pressure on the mental health of individuals (due to social distancing and lock-down measures). The pandemic is also posing severe challenges to the scientific community, with scholars under pressure to respond to policymakers’ demands for advice despite the absence of adequate, trusted data. Understanding the pandemic requires fine-grained data representing specific local conditions and the social reactions of individuals. While experts have built simulation models to estimate disease trajectories that may be enough to guide decision-makers to formulate policy measures to limit the epidemic, they do not cover the full behavioural and social complexity of societies under pandemic crisis. Modelling that has such a large potential impact upon people’s lives is a great responsibility. This paper calls on the scientific community to improve the transparency, access, and rigour of their models. It also calls on stakeholders to improve the rapidity with which data from trusted sources are released to the community (in a fully responsible manner). Responding to the pandemic is a stress test of our collaborative capacity and the social/economic value of research.

This article examines gender bias in peer review with complete data on 145 journals in various fields of research, including about 1.7 million authors and 740,000 referees. We reconstructed three possible sources of bias, i.e., the editorial selection of referees, referee recommendations, and editorial decisions, and examined all their possible relationships. In line with previous research, we found that editors were sensitive to gender homophily in that they tended to match authors and referee by gender systematically. Results showed that in general manuscripts written by women as solo authors or co-authored by women are treated even more favorably by referees and editors. This is especially so in biomedicine and health journals, whereas women were treated relatively less favorably in social science & humanities journals, i.e., the field in which the ratio of female authors was the highest in our sample. Although with some caveat, our findings suggest that peer review and editorial processes in scholarly journals do not penalize manuscripts by women. However, considering the complex social nature of gender prejudices, journals should increase gender diversity among reviewers and editors as a means of correcting signals potentially biasing the perceptions of authors and referees.

This article examines information-search heuristics and communication patterns in an online forum of investors during a period of market uncertainty. Global connections, real-time communication, and technological sophistication have created an unpredictable market environment. As such, investors try to deal with semantic, strategic, and operational uncertainty by following heuristics that reduce information redundancy. In this study, we have tried to find traces of cognitive communication heuristics in a large-scale data set including 8 years of online posts (2004–2012) for a forum of Italian investors. We identified various market volatility conditions on a daily basis to understand the influence of market uncertainty on cognitive and communication processes. We found that investors communicated more dynamically when the market was unstable, while they were more prone to anchor heuristic when market uncertainty was invariant. Furthermore, abnormal market trends triggered more availability-based communication patterns. We also found that expertise matters. This would suggest that online communities need intelligent, context-specific tools to support partner selection and stimulate nonredundant communication.

This paper looks at peer review as a cooperation dilemma through a game-theory framework. We built an agent-based model to estimate how much the quality of peer review is influenced by different resource allocation strategies followed by scientists dealing with multiple tasks, i.e., publishing and reviewing. We assumed that scientists were sensitive to acceptance or rejection of their manuscripts and the fairness of peer review to which they were exposed before reviewing. We also assumed that they could be realistic or excessively over-confident about the quality of their manuscripts when reviewing. Furthermore, we assumed they could be sensitive to competitive pressures provided by the institutional context in which they were embedded. Results showed that the bias and quality of publications greatly depend on reviewer motivations but also that context pressures can have a negative effect. However, while excessive competition can be detrimental to minimising publication bias, a certain level of competition is instrumental to ensure the high quality of publication especially when scientists accept reviewing for reciprocity motives.

Referrals and information flow distort market mechanisms of hiring in the labor market, but they might assist employers under asymmetric information in finding better alternatives. This paper investigates whether an impartial information flow between employers in a cyclic network structure could generate more discrimination than when no information is exchanged between employers. We set up an artificial labor market in which there was no average quality difference between two categories of workers. We asked participants to play the role of employers and examined the partiality of their hiring choices. Results showed that discrimination was prevalent in all conditions. Higher standards by the employers for the quality of workers increased discrimination as did the presence of referrals from workers. Unexpectedly, impartial information flow in a cyclic network of employers did not help to decrease discrimination. We also showed that these mechanisms interact with and subdue each other in complex ways.

This paper aims to examine the influence of authors’ reputation on editorial bias in scholarly journals. By looking at eight years of editorial decisions in four computer science journals, including 7179 observations on 2913 submissions, we reconstructed author/referee-submission networks. For each submission, we looked at reviewer scores and estimated the reputation of submission authors by means of their network degree. By training a Bayesian network, we estimated the potential effect of scientist reputation on editorial decisions. Results showed that more reputed authors were less likely to be rejected by editors when they submitted papers receiving negative reviews. Although these four journals were comparable for scope and areas, we found certain journal specificities in their editorial process. Our findings suggest ways to examine the editorial process in relatively similar journals without recurring to in-depth individual data, which are rarely available from scholarly journals.

This article provides a quantitative analysis of peer review as an emerging field of research by revealing patterns and connections between authors, fields and journals from 1950 to 2016. By collecting all available sources from Web of Science, we built a dataset that included approximately 23,000 indexed records and reconstructed collaboration and citation networks over time. This allowed us to trace the emergence and evolution of this field of research by identifying relevant authors, publications and journals and revealing important development stages. Results showed that while the term “peer review” itself was relatively unknown before 1970 (“referee” was more frequently used), publications on peer review significantly grew especially after 1990. We found that the field was marked by three development stages: (1) before 1982, in which most influential studies were made by social scientists; (2) from 1983 to 2002, in which research was dominated by biomedical journals, and (3) from 2003 to 2016, in which specialised journals on science studies, such as Scientometrics, gained momentum frequently publishing research on peer review and so becoming the most influential outlets. The evolution of citation networks revealed a body of 47 publications that form the main path of the field, i.e., cited sources in all the most influential publications. They could be viewed as the main corpus of knowledge for any newcomer in the field.

Peer review is the defining feature of scholarly communication. In a 2018 survey of more than 11, 000 researchers, 98% said that they considered peer review important or extremely important for ensuring the quality and integrity of scholarly communication.

While recent surveys show that most stakeholders recognise the importance of peer review to the publication process, there is a lack of systematic research on the topic. In a period of hyper-competition for resources, with perverse incentives that lead to academic capitalism and a “publish or perish” mentality, the lack of robust and cumulative research on approaches, models and practices of peer review can slow down efforts towards fostering research integrity and the credibility of scholarly communication. A major challenge in studying peer review systematically is the lack of available data. While data sharing in scientific research has made relevant progress in certain fields, the lack of infrastructures to promote the sharing of peer review data among publishers, journals and academic scholars, the challenges posed by privacy and data protection legislation, and the perceived lack of incentives for publishers, learned societies and journals to share data, have all hampered efforts in this important domain. While public authorities, learned societies and publishers may face different priorities, incentives and obstacles regarding data sharing, the time has come to call to action all stakeholders who play a part in this field. In this paper, we argue that an infrastructure for data sharing is needed to stimulate independent, collaborative, public research on peer review and we suggest measures and initiatives to set up a collaborative effort towards this goal.

How one builds, checks, validates and interprets a model depends on its ‘purpose’. This is true even if the same model code is used for different purposes. This means that a model built for one purpose but then used for another needs to be re-justified for the new purpose and this will probably mean it also has to be re-checked, re-validated and maybe even re-built in a different way. Here we review some of the different purposes for a simulation model of complex social phenomena, focusing on seven in particular: prediction, explanation, description, theoretical exploration, illustration, analogy, and social interaction. The paper looks at some of the implications in terms of the ways in which the intended purpose might fail. This analysis motivates some of the ways in which these ‘dangers’ might be avoided or mitigated. It also looks at the ways that a confusion of modelling purposes can fatally weaken modelling projects, whilst giving a false sense of their quality. These distinctions clarify some previous debates as to the best modelling strategy (e.g. KISS and KIDS). The paper ends with a plea for modellers to be clear concerning which purpose they are justifying their model against.

Peer review is a process used in the selection of manuscripts for journal publication and proposals for research grant funding. Though widely used, peer review is not without flaws and critics. Performing large-scale experiments to evaluate and test correctives and alternatives is difficult, if not impossible. Thus, many researchers have turned to simulation studies to overcome these difficulties. In the last ten years this field of research has grown significantly but with only limited attempts to integrate disparate models or build on previous work. Thus, the resulting body of literature consists of a large variety of models, hinging on incompatible assumptions, which have not been compared, and whose predictions have rarely been empirically tested. This scoping review is an attempt to understand the current state of simulation studies of peer review. Based on 46 articles identified through literature searching, we develop a proposed taxonomy of model features that include model type (e.g. formal models vs. ABMs or other) and the type of modeled peer review system (e.g. peer review in grants vs. in journals or other). We classify the models by their features (including some core assumptions) to help distinguish between the modeling approaches. Finally, we summarize the models’ findings around six general themes: decision-making, matching submissions/reviewers, editorial strategies; reviewer behaviors, comparisons of alternative peer review systems, and the identification and addressing of biases. We conclude with some open challenges and promising avenues for future modeling work. Science Foundation Ireland

Group size can potentially affect collective activity and individual propensity to contribute to collective goods. Mancur Olson, in his Logic of Collective Action, argued that individual contribution to a collective good tends to be lower in groups of large size. Today, online communication platforms represent an interesting ground to study such collaborative dynamics under possibly different conditions (e.g., lower costs related to gather and share information). This paper examines the relationship between group size and activity in an online financial forum, where users invest time in sharing news, analysis and comments with other investors. We looked at about 24 million messages shared in more than ten years in the finanzaonline.com online forum. We found that the relationship between the number of active users and the number of posts shared by those users is of the power type (with exponent α > 1 ) and is subject to periodic fluctuations, mostly driven by hour-of-the-day and day-of-the-week effects. The daily patterns of the exponent showed a divergence between working week and weekend days. In general, the exponent was lower before noon, where investors are typically interested in market news, higher in the late afternoon, where markets are closing and investors need better understanding of the situation. Further research is needed, especially at the micro level, to dissect the mechanisms behind these regularities.

L’approche par modeles multi-agents a travers quelques ouvrages fondamentaux L’article analyse quelques monographies fondamentales qui mettent en evidence la pertinence de la simulation multi-agents pour l’analyse sociologique. Ces ouvrages ont ete selectionnes au sein de travaux qui portent sur la cooperation, les dynamiques sociales et les normes. Ils montrent l’importance de modeliser les comportements complexes des acteurs et leurs interactions pour comprendre les regularites sociales ainsi que les raisons pour lesquelles la modelisation et l’abstraction sont importantes pour l’analyse sociologique. La modelisation multi-agents peut nous aider a produire des theories des phenomenes sociaux plus coherentes et verifiables et nous permet de mieux organiser les theories avant de les tester et en vue de les repliquer. Enfin, dans l’esprit d’une approche collaborative, cet article argumente en faveur du besoin de liens plus etroits entre les approches experimentales et la sociologie.

This chapter aims to discuss certain limitations of the dominant equilibrium thinking in policy and explore more complexity-friendly alternatives. If societies and markets are viewed as complex, non-equilibrium systems, understanding nonlinear, adaptive and evolving patterns emerging from agent behaviour in network structures is fundamental for policy purposes. This requires improved realism of the behavioural and social foundations on which policies are based. We must also reconsider the mantra of incentivisation, institutional design and the top-down regulation that typically dominates conventional policy. Recent cases of financial market regulation and health policies can help us to understand the importance of looking at the subtle ways in which people or organisations behave when exposed to social influence, and pre-existing social norms and network externalities. Changing the current policy narrative and exploring complexity-friendly concepts, instruments and methods requires a shift of focus of policy-making from forecast and prediction of system equilibrium in order to understand and manage complex social systems better.

This paper investigates the fate of manuscripts that were rejected from JASSS-The Journal of Artificial Societies and Social Simulation, the flagship journal of social simulation. We tracked 456 manuscripts that were rejected from 1997 to 2011 and traced their subsequent publication as journal articles, conference papers or working papers. We compared the impact factor of the publishing journal and the citations of those manuscripts that were eventually published against the yearly impact factor of JASSS and the number of citations achieved by the JASSS mean and top cited articles. Only 10% of the rejected manuscripts were eventually published in a journal that was indexed in the Web of Science, although most of the rejected manuscripts were published elsewhere. Being exposed to more than one round of reviews before rejection, having received a more detailed reviewer report and being subjected to higher inter-reviewer disagreement were all associated with the number of citations received when the manuscript was eventually published. This indicates that peer review could contribute to increasing the quality even of rejected manuscripts.

Certain features of the social environment could maintain and even improve not only psychological well-being, but also health and cognition of the elderly. We tested the association between social network characteristics and the number of chronic diseases in the elderly. A randomized sample of the elderly population of Brescia, Italy, was evaluated (N = 200, age ≥65 years). We performed a comprehensive geriatric assessment, including information on socio-demographic variables (family, friendships, and acquaintance contacts). We measured each person’s social network, i.e., degree, efficiency, and variety. The sample included 118 women and 82 men, mean age 77.7 years. The mean number of chronic diseases was 3.5. A higher social network degree, i.e., more social connections, was associated with fewer diseases. We also found that having more contacts with people similar to each other or intense relationships with people who do not know each other were associated with fewer diseases. More healthy people tend to share certain characteristics of social networks. Our study indicates that it is important to look at diseases and health as complex phenomena, which requires integrating different levels of analysis.

This article aims to introduce a special issue on "Scientometrics of peer review", which collects papers originally presented at workshops and conferences organised by the COST ACTION TD1306 "New frontiers of peer review". Peer review is the cornerstone of science and is one of the underlying processes that bring about publication traces that are at the heart of bibliometric studies. Unfortunately, despite its importance, quantitative studies on peer review are still poorly developed, often due to lack of data. The issue aims to promote the establishment of peer review as an interdisciplinary field of research and stimulate further quantitative research.