We analyze small stories in a focus group on immigration to understand how small stories offer resources for group interaction in zero-history groups. Our analysis reveals two new functions of stories in deliberation: through small stories participants establish interactional identities (notably the role of expert) and reveal social categories relevant to the issue. Attending to how stories are elicited by other participants also reveals how group members use ventriloquism to have their arguments voiced by people representing particular social categories as a result of their small stories. This empirical analysis raises a normative question for public deliberation scholars: If narratives are vital to public deliberation, what happens when some people have relevant stories to tell and others do not? We suggest how small stories research can help deliberative theorists consider this question.
This study develops a context-grounded ideal about how citizens ought to communicate in legislative hearings about contentious issues. We begin with an overview of the dominant model of good citizen discourse, democratic deliberation, and argue why it is an inappropriate norm for public hearings in state legislative bodies. After overviewing grounded practical theory (GPT), the meta-theoretical approach used, and providing background on the demands of public meetings, we describe the public hearing that is the focal data. That hearing was the 18-hour, 2009 Hawaii hearing on a bill that proposed to recognize committed relationships of same-sex couples through civil unions. The analysis of citizen testimony evidences a discourse strategy, democracyappealing partisanship, which speakers on both sides of the issue used to manage the challenges they confronted in speaking out. This strategy involved advocating strongly for one viewpoint as an appeal to either majority rule or minority rights and/or either freedom of religion or separation of church and state were made. In concluding, we describe the problem to which this strategy is responsive, justify the norm of democracy-appealing partisanship, and offer implications for future studies using GPT.
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