The Dynamic Relationship Between Freedom of Speech and Equality

This Article examines the dynamic intersection between freedom of speech and equal protection, with a particular focus on the race and LGBT equality movements. Unlike other works on expression and/or equality, the Article emphasizes the relational and bi-directional connections between freedom of speech and equal protection. Freedom of speech has played a critical role in terms of advancing constitutional equality. However, with regard to both race and LGBT equality, free speech rights also failed in important respects to facilitate equality claims and movements. Advocacy and agitation on behalf of equality rights have also left indelible positive and negative marks on free speech doctrines, principles, and rights. The free speech-equality relationship underscores several important lessons regarding reliance on speech rights to advance constitutional equality. Moreover, through a comparative analysis, the Article demonstrates that freedom of speech intersects in distinctive ways with different types of equalities. The Article’s general lessons and comparative observations carry important implications for future equality movements, including the current campaign for transgender equality

Forming Probably Stable Communities with Limited Interactions

A community needs to be partitioned into disjoint groups; each community member has an underlying preference over the groups that they would want to be a member of. We are interested in finding a stable community structure: one where no subset of members $S$ wants to deviate from the current structure. We model this setting as a hedonic game, where players are connected by an underlying interaction network, and can only consider joining groups that are connected subgraphs of the underlying graph. We analyze the relation between network structure, and one's capability to infer statistically stable (also known as PAC stable) player partitions from data. We show that when the interaction network is a forest, one can efficiently infer PAC stable coalition structures. Furthermore, when the underlying interaction graph is not a forest, efficient PAC stabilizability is no longer achievable. Thus, our results completely characterize when one can leverage the underlying graph structure in order to compute PAC stable outcomes for hedonic games. Finally, given an unknown underlying interaction network, we show that it is NP-hard to decide whether there exists a forest consistent with data samples from the network.Comment: 11 pages, full version of accepted AAAI-19 pape