Does Empirical Embeddedness Matter? Methodological Issues on Agent-Based Models for Analytical Social Science

The paper deals with the use of empirical data in social science agent-based models. Agent-based models are too often viewed just as highly abstract thought experiments conducted in artificial worlds, in which the purpose is to generate and not to test theoretical hypotheses in an empirical way. On the contrary, they should be viewed as models that need to be embedded into empirical data both to allow the calibration and the validation of their findings. As a consequence, the search for strategies to find and extract data from reality, and integrate agent-based models with other traditional empirical social science methods, such as qualitative, quantitative, experimental and participatory methods, becomes a fundamental step of the modelling process. The paper argues that the characteristics of the empirical target matter. According to characteristics of the target, ABMs can be differentiated into case-based models, typifications and theoretical abstractions. These differences pose different challenges for empirical data gathering, and imply the use of different validation strategies.Agent-Based Models, Empirical Calibration and Validation, Taxanomy of Models

The Agent-Based Modeling Approach through Some Foundational Monographs

L’article analyse quelques monographies fondamentales qui mettent en évidence la pertinence de la simulation multi-agents pour l’analyse sociologique. Ces ouvrages ont été sélectionnés au sein de travaux qui portent sur la coopération, les dynamiques sociales et les normes. Ils montrent l’importance de modéliser les comportements complexes des acteurs et leurs interactions pour comprendre les régularités sociales ainsi que les raisons pour lesquelles la modélisation et l’abstraction sont importantes pour l’analyse sociologique. La modélisation multi-agents peut nous aider à produire des théories des phénomènes sociaux plus cohérentes et vérifiables et nous permet de mieux organiser les théories avant de les tester et en vue de les répliquer. Enfin, dans l’esprit d’une approche collaborative, cet article argumente en faveur du besoin de liens plus étroits entre les approches expérimentales et la sociologie

A (Computational) Social Science Perspective to Societal Transitions

This paper aims to illustrate how social sciences, sociology in particular, have theorized on societal transitions. The first section introduces some preliminary definitions. The assumption is that a societal transition is more than a social, economic or technological change. It is a large-scale and long-term macro process through which a given social system radically changes its structural basis, in terms of new socio-technical practices, governance rules, social and economic institutions, cultural frames, and patterns of social life. The second section provides an excursus on social science accounts on transitions. In particular, the attention has been given to Norbert Elias' famous study on the rise and fall of the court society in France, between 17th and 18th century and to Manuel Castells' recent analysis of the emergence of the network society. The third section discusses problems and challenges of standard approaches and suggests some building blocks of societal transition models, taken from complexity and social simulation literature. The concluding section suggests some way-forward measures towards a computational social science approach to societal transition

Embedded, scattered, confused minds. What do hyper-conductive markets impose on investors’ social intelligence

This article discusses the observation theory developed by Elena Esposito, especially emphasising her critique of embeddedness. My understanding is that observation theory, if pushed to its limits, implies a never ending, infinite regression of meaning, cannot help to fully understand market behaviour. This is true for ‘scientific observers’ but also for ‘field observers’, e.g.., economic agents. Recent empirical findings indicate that the latter deal with (semantic, ontological and strategic) uncertainty, which is amplified by hyper-conductive, ICT-boosted, global markets, by drastically simplifying their strategies, adaptively segmenting and re-segmenting their epistemic, social “observation” space and creatively exploiting heuristics, emotions and social information. These findings seem to be more compatible with the idea of a continuous process of dis/re-embedding economic action. I argue that the involvement vs. detachment analogy formulated by Norbert Elias in his sociology of science studies could help us to develop an observation theory that does not merge individual and social dimensions and is more compatible with empirical evidence

Local Economic Development Initiatives from the Bottom-Up: The Role of Community Development Corporations

This paper deals with the pivotal role played by community development corporations (CDCs) in local economic initiatives from the bottom-up. These non-profit organizations are challenging the top-down approach of political decision making, mobilizing community assets, connecting inside and outside resources, synthesizing visions, expertise and methods from private, public and community sectors. In doing so, they are demonstrating the relevance of non-profit organizations and institutions in fostering social capital and promoting collective action across different sectors and actors. To illustrate these arguments, this paper has reported two case studies of local economic development initiatives in North America that are centered on two CDCs. The positive effects and critical points of CDCs have been addressed

Social Entrepreneurship and Economic Development in Silicon Valley: A Case-Study on The Joint-Venture: Silicon Valley Network

Social entrepreneurs are playing a pivotal role in promoting intersector initiatives to address economic and social challenges in regions and local communities. This generates social capital to support an initiative-oriented collaboration framework among participants and across sectors. Such intersectoral initiatives are of paramount importance for the capacity of a region/community to set up innovative solutions to socioeconomic problems from the bottom-up, going beyond the limits of markets and government institutions. This is increasingly happening not only in depressed but also in developed regions and communities, such as Silicon Valley. This article reports on the Joint Venture: Silicon Valley Network, a nonprofit organization launched in 1992 to promote a series of intersectoral initiatives at the edge of the economy, society, and environment in Silicon Valley

The Impact of Agent-Based Models in the Social Sciences after 15 Years of Incursions

This paper provides an overview on the impact of agent-based models in the social sciences. It focuses on the reasons why agent-based models are seen as important innovations in the recent decades. It is aimed to evaluate the impact of this innovation on various disciplines, such as economics, sociology, anthropology, and behavioural sciences. It discusses the advances it contributed to achieve and illustrates some comparatively new fields to which it gave rise. Finally, it emphasizes some research issues that need to be addressed in the future

Times, Noise and Institutional Complexity. A Comment on Graham Room’s Essay on the “Contingent Historical Model” of Social Dynamics

This comment on the essay \u201cThe Empirical Investigation of Non-Linear Dynamics in the Social World. Ontology, Methodology and Data\u201d, by Graham Room, focuses on the challenge of understanding institutional change in complex social systems. It discusses the evolutionary foundations of Room\u2019s \u201cContingent Historical Model\u201d by questioning the bio-social divide on selection mechanisms. It concentrates on Room\u2019s concept of temporalities of institutional change and discusses the role of noise