Hackathons bring developers, artists and designers together around a shared challenge: ideate, plan and create an application in a highly constrained time frame. A way to socialize, solve problems, and strengthen soft and hard skills, hackathons have grown tremendously in popularity in the last half decade. Despite this growth, it has been noted that females do not participate in hackathons with the same frequency as males. Some theorize that the hackathon culture is intimidating, does not appeal to women, or that it acts to amplify pre-existing cultural biases in computing. In this paper we introduce an alternative format for hackathons to address these issues. Think Global Hack Local (TGHL) is a non-competitive, communitybased hackathon that connects non-profit organizations with student developers. Students donate a weekend to solve problems that these organizations otherwise lack the resources to solve. To date, there have been two TGHL hackathons, and we have observed many interesting divergences within the culture of TGHL in comparison to other hackathons. Response has been positive, and nearly all of them indicate that they would do it again. By adopting some of these ideas, we believe that hackathons can become an environment that is more inclusive and fun for all.

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Psychological investigations have led to considerable insight into the working of the human language comprehension system. In this article, we look at a set of principles derived from psychological findings to argue for a particular organization of linguistic knowledge along with a particular processing strategy and present a computational model of sentence processing based on those principles. Many studies have shown that human sentence comprehension is an incremental and interactive process in which semantic and other higher-level information interacts with syntactic information to make informed commitments as early as possible at a local ambiguity. Early commitments may be made by using topdown guidance from knowledge of different types, each of which must be applicable independently of others. Further evidence from studies of error recovery and delayed decisions points toward an arbitration mechanism for combining syntactic and semantic information in resolving ambiguities. In order to account for all of the above, we propose that all types of linguistic knowledge must be represented in a common form but must be separable so that they can be applied independently of each other and integrated at processing time by the arbitrator. We present such a uniform representation and a computational model called COMPERE based on the representation and the processing strategy.