An Extension of Combinatorial Contextuality for Cognitive Protocols.

This article extends the combinatorial approach to support the determination of contextuality amidst causal influences. Contextuality is an active field of study in Quantum Cognition, in systems relating to mental phenomena, such as concepts in human memory. In the cognitive field of study, a contemporary challenge facing the determination of whether a phenomenon is contextual has been the identification and management of disturbances. Whether or not said disturbances are identified through the modeling approach, constitute causal influences, or are disregardableas as noise is important, as contextuality cannot be adequately determined in the presence of causal influences. To address this challenge, we first provide a formalization of necessary elements of the combinatorial approach within the language of canonical causal models. Through this formalization, we extend the combinatorial approach to support a measurement and treatment of disturbance, and offer techniques to separately distinguish noise and causal influences. Thereafter, we develop a protocol through which these elements may be represented within a cognitive experiment. As human cognition seems rife with causal influences, cognitive modelers may apply the extended combinatorial approach to practically determine the contextuality of cognitive phenomena.

Trust, but verify: social media models for disaster management.

A lack of trust in the information exchanged via social media may significantly hinder decisionmaking by community members and emergency services during disasters. The need for timely information at such times, though, challenges traditional ways of establishing trust. This paper, building on a multi-year research project that combined social media data analysis and participant observation within an emergency management organisation and in-depth engagement with stakeholders across the sector, pinpoints and examines assumptions governing trust and trusting relationships in social media disaster management. It assesses three models for using social media in disaster management-information gathering, quasi-journalistic verification, and crowdsourcing-in relation to the guardianship of trust to highlight the verification process for content and source and to identify the role of power and responsibilities. The conclusions contain important implications for emergency management organisations seeking to enhance their mechanisms for incorporating user-generated information from social media sources in their disaster response efforts.