  The design of mechanisms that encourage pro-social behaviours in populations
of self-regarding agents is recognised as a major theoretical challenge within
several areas of social, life and engineering sciences. When interference from
external parties is considered, several heuristics have been identified as
capable of engineering a desired collective behaviour at a minimal cost.
However, these studies neglect the diverse nature of contexts and social
structures that characterise real-world populations. Here we analyse the impact
of diversity by means of scale-free interaction networks with high and low
levels of clustering, and test various interference mechanisms using
simulations of agents facing a cooperative dilemma. Our results show that
interference on scale-free networks is not trivial and that distinct levels of
clustering react differently to each interference mechanism. As such, we argue
that no tailored response fits all scale-free networks and present which
mechanisms are more efficient at fostering cooperation in both types of
networks. Finally, we discuss the pitfalls of considering reckless interference
mechanisms.
