Into the Streets: Day 1 - Session 1: Different ages of activism

A chant of the early gay & lesbian movement – “Out of the Closets & Into the Streets! Out of the Bars & Into the Streets!” provides the theme for a major conference to be held at the University of Technology, Sydney on Friday 24 & Saturday 25 September 2010 on the beginnings of open lesbian and gay activism in Australia. With the public announcement of the founding of Campaign Against Moral Persecution, or CAMP, in September 1970, John Ware and Christabel Poll became the first openly self-identified homosexuals in Australia. The consequences of their action went far beyond that of establishment of one organisation -- it marked the beginning of a gay and lesbian movement in this country. This conference aims to explore the social, political and cultural background that led to the announcement, and its wider repercussions and consequences. While there will be a focus on Sydney, we want this to be a national conference. Experiences around Australia provide an important contrast and illustrate different models of activism. Within a year of the formation of CAMP, an informal network of organisations had grown up around Australia. Other states too mirrored the split in the movement that took place with the formation of the (supposedly) more radical Gay Liberation groups, especially on university campuses, and the beginnings of an autonomous radical lesbian movement around Australia.Reverse activism of younger lesbians – Natalie Dabarera and Chantel Cotterell Citizen Glynn: an unemployed leather-loving gay rights advocate who gave us the Sydney Star Observer – Dominic O’Grady Chair: Rebecca JenningsSydney’s Pride History Grou

Dynamics of belief theoretic agent opinions under bounded confidence

Soft evidence sources play a critical role in social networks and similar settings, where subjective evidence and opinions are the norm. Study of opinion dynamics (including consensus and cluster formation) in these scenarios requires agent models that can capture the types of uncertainties and nuances characteristic of soft evidence (human-generated input, subjective evidence, etc.). To address the corresponding challenges, we employ a Dempster-Shafer (DS) belief theoretic agent model to explore opinion dynamics under bounded confidence. The proposed model further captures the notions of global affinity and the nature of persuasion of agents in social judgement theory. The paper develops several new results and these results regarding formation of clusters and consensus of agent opinions are verified with the aid of several numerical studies accompanied by bifurcation diagrams

DS-based uncertain implication rules for inference and fusion applications

Numerous applications rely on implication rules either as models of causal relations among data, or as components of their reasoning and inference systems. Although mature and robust models of implication rules already exist for "perfect" (e.g., boolean) scenarios, there is still a need for improving implication rule models when the data (or system models) are uncertain, ambiguous, vague, or incomplete. Decades of research have produced models for probabilistic and fuzzy systems. However, the work on uncertain implication rules under the Dempster-Shafer (DS) theoretical framework can still be improved. Given that DS theory provides increased robustness against uncertain/incomplete data, and that DS models can easily be converted into probabilistic and fuzzy models, a DS-based implication rule that is consistent with classical logic would definitely improve inference methods when dealing with uncertainty. We introduce a DS-based uncertain implication rule that is consistent with classical logic. This model satisfies reflexivity, contrapositivity, and transitivity properties, and is embedded into an uncertain logic reasoning system that is itself consistent with classical logic. When dealing with "perfect" (i.e., no uncertainty) data, the implication rule model renders the classical implication rule results. Furthermore, we introduce an ambiguity measure to track degeneracy of belief models throughout inference processes. We illustrate the use and behavior of both the uncertain implication rule and the ambiguity measure in a human-robot interaction problem