Collective action and civil disobedience: the anti-GMO campaign of the Faucheurs volontaires

Civil disobedience has hitherto enjoyed only a relatively marginal place in the repertoires of French social movements, but has recently emerged as a key rallying frame for social mobilization, especially among environmental and counter-globalization movements. This paper examines the theory and practice of civil disobedience in the French context through an analysis of one such movement, the anti-GM Faucheurs Volontaires. Discussing the highly controversial campaign's positioning as 'civic disobedience', the article examines contested discourses of violence surrounding crop destruction, and the state responses to action, before asking what the campaign's claims to Republican civism mean for traditional notions of the relationship between state and challenging groups in France. It argues that framing action as civil disobedience is central to attempts to construct political and popular legitimacy, in terms of the campaign's national, international, and sectoral goals.

Harnessing diversity and collective action in the top management team

Diversity has become an important issue at all levels of the company from the boardroom to the back office. It is increasingly apparent that diversity is vital to productivity, with academic research indicating an important link between diverse top management team (TMT) composition and corporate performance. However, the nature of this link remains elusive, as there is little accessible research that can help top teams to evaluate how diversity impacts on their strategic capacity. This paper seeks to fill this gap by developing a conceptual framework, illustrated with case examples, to explain the relationships between TMT diversity and TMT collective action. As collective action is difficult to attain from top teams that are high in diversity, six practical processes are developed from this framework for establishing and exploiting top team strategic capacity. The paper concludes by outlining the theoretical implications of the framework. © Elsevier Ltd. All rights reserved.

Can we observe collective neuronal activity from macroscopic aggregate signals?

The fundamental problem faced by noninvasive neuroimaging techniques such as EEG/MEG1 is to elucidate functionally important aspects of the microscopic neuronal network dynamics from macroscopic aggregate measurements. Due to the mixing of the activities of large neuronal populations in the observed macroscopic aggregate, recovering the underlying network that generates the signal in the absence of any additional information represents a considerable challenge. Recent MEG studies have shown that macroscopic measurements contain sufficient information to allow the differentiation between patterns of activity, which are likely to represent different stimulus-specific collective modes in the underlying network (Hadjipapas, A., Adjamian, P., Swettenham, J.B., Holliday, I.E., Barnes, G.R., 2007. Stimuli of varying spatial scale induce gamma activity with distinct temporal characteristics in human visual cortex. NeuroImage 35, 518–530). The next question arising in this context is whether aspects of collective network activity can be recovered from a macroscopic aggregate signal. We propose that this issue is most appropriately addressed if MEG/EEG signals are to be viewed as macroscopic aggregates arising from networks of coupled systems as opposed to aggregates across a mass of largely independent neural systems. We show that collective modes arising in a network of simulated coupled systems can be indeed recovered from the macroscopic aggregate. Moreover, we show that nonlinear state space methods yield a good approximation of the number of effective degrees of freedom in the network. Importantly, information about hidden variables, which do not directly contribute to the aggregate signal, can also be recovered. Finally, this theoretical framework can be applied to experimental MEG/EEG data in the future, enabling the inference of state dependent changes in the degree of local synchrony in the underlying network.