Marking their own homework: The pragmatic and moral legitimacy of industry self-regulation

When is industry self-regulation (ISR) a legitimate form of governance? In principle, ISR can serve the interests of participating companies, regulators and other stakeholders. However, in practice, empirical evidence shows that ISR schemes often under-perform, leading to criticism that such schemes are tantamount to firms marking their own homework. In response, this paper explains how current management theory on ISR has failed to separate the pragmatic legitimacy of ISR based on self-interested calculations, from moral legitimacy based on normative approval. The paper traces three families of management theory on ISR and uses these to map the pragmatic and moral legitimacy of ISR schemes. It identifies tensions between the pragmatic and moral legitimacy of ISR schemes, which the current ISR literature does not address, and draws implications for the future theory and practice of ISR

Cortical Resonance Frequencies Emerge from Network Size and Connectivity

Neural oscillations occur within a wide frequency range with different brain regions exhibiting resonance-like characteristics at specific points in the spectrum. At the microscopic scale, single neurons possess intrinsic oscillatory properties, such that is not yet known whether cortical resonance is consequential to neural oscillations or an emergent property of the networks that interconnect them. Using a network model of loosely-coupled Wilson-Cowan oscillators to simulate a patch of cortical sheet, we demonstrate that the size of the activated network is inversely related to its resonance frequency. Further analysis of the parameter space indicated that the number of excitatory and inhibitory connections, as well as the average transmission delay between units, determined the resonance frequency. The model predicted that if an activated network within the visual cortex increased in size, the resonance frequency of the network would decrease. We tested this prediction experimentally using the steady-state visual evoked potential where we stimulated the visual cortex with different size stimuli at a range of driving frequencies. We demonstrate that the frequency corresponding to peak steady-state response inversely correlated with the size of the network. We conclude that although individual neurons possess resonance properties, oscillatory activity at the macroscopic level is strongly influenced by network interactions, and that the steady-state response can be used to investigate functional networks