Norms, status and the dynamics of advice networks: A case study

Abstract

International audienceThe issue of the influence of norms on behavior is as old as sociology itself. This paper explores the effect of normative homophily (i.e. “sharing the same normative choices”) on the evolution of the advice network among lay judges in a courthouse. 0020 and 0025 social exchange theory suggests that members select advisors based on the status of the advisor. Additional research shows that members of an organization use similarities with others in ascribed, achieved or inherited characteristics, as well as other kinds of ties, to mitigate the potentially negative effects of this strong status rule. We elaborate and test these theories using data on advisor choice in the Commercial Court of Paris. We use a jurisprudential case about unfair competition (material and “moral” damages), a case that we submitted to all the judges of this court, to test the effect of normative homophily on the selection of advisors, controlling for status effects. Normative homophily is measured by the extent to which two judges are equally “punitive” in awarding damages to plaintiffs. Statistical analyses combine longitudinal advice network data collected among the judges with their normative dispositions. Contrary to what could be expected from conventional sociological theories, we find no pure effect of normative homophily on the choice of advisors. In this case, therefore, sharing the same norms and values does not have, by itself, a mitigating effect and does not contribute to the evolution of the network. We argue that status effects, conformity and alignments on positions of opinion leaders in controversies still provide the best insights into the relationship between norms, structure and behavior

Opinion transmission in organizations: an agent-based modeling approach

“…Previous empirical research (Lazega et al 2012) indicates that the dynamics of the advice network is driven by status, a notion that includes seniority as one of its key components and loosely corresponds to our experience, rather than by opinion homophily, and that the judges are often divided into opposing camps on essential judicial questions (Lazega et al 2012;Lazega et al 2011). Our study reveals possible mechanisms through which, over the centurieslong duration of activity of the Court, transmission of opinions driven by seniors' primacy eventually gives rise to polarization.…”

“…An advice network is defined as "the pattern of relations among [organizational] members in which one member seeks advice from another member" (Athanassiou & Nigh, 1999: 86) and develops over time as organizational members seek assistance, guidance, information, and opportunities for problem solving (Gibbons, 2004). Advice networks have been studied to understand knowledge transmission (Reagans & McEvily, 2003), changes of organizational strategies (McDonald & Westphal, 2003), changes in attitude toward technology (Burkhardt, 1994) and status differentials (Lazega et al, 2012).…”

“…Available empirical evidence supports this approach: indeed a dataset of the advice network of judges, collected at three points in time (2000, 2002 and 2005), reveals a correlation between network structure, formal hierarchy of the institution (in particular, its division into Chambers, annual rotation of members across Chambers, rules of attribution of senior management roles) and normative views, which could hardly result from random matching; Rouchier & Tubaro (2011) show that an agent-based simulation based on Deffuant's model and modified to include membership turnover, but still assuming randomness in the formation of inter-personal ties, does not fit the data well. Instead, other factors are found to play a role in network tie formation, notably seniority and the internal hierarchy of the institution, as well as homophily, including opinion homophily (Lazega, Lemercier & Mounier 2006;Lazega, Mounier & Tubaro 2011;Lazega, Mounier, Snijders & Tubaro 2012). …”

Emergence of multiplex mobile phone communication networks across rural areas: An Ethiopian experiment

“…Social status and social capital have been hypothesized to affect such endogenous tendencies in advice networks (Agneessens & Wittek, 2012;Lazega et al, 2012). From the status perspective, giving advice generates prestige, whereas requesting information decreases it.…”

IPBES, an inclusive institution? Challenging the integration of stakeholders in a science-policy interface

“…We thus questioned 48 participants during the stakeholder days of the plenary session, asking them the following sociometric question: When you want to take a position (or produce a position paper) on a subject related to IPBES who are the people from the list of 48 actors whom you ask for advice? We then constructed some groups according to the relational proximity of the stakeholders in the directed advice network (Lorrain and White 1971, Lazega and Pattison 1999, Lazega et al 2012. Based on the matrix of the stakeholder advice network we calculated the relational proximity between two individuals within the network using Ward's method that provides hierarchical clustering (cf.…”