1. Deliberative Democracy and the PINet Project JOHN GASTIL D EPT. OF C OMM. A RTS & S CIENCES T HE P ENNSYLVANIA S TATE U NIVERSITY F EBRUARY 24, 2013

2. Articles on Deliberative Democracy Number of peer-reviewed articles with search terms in record fields. Terms = (Deliberation OR Deliberative) AND (Civic OR Citizen OR Political OR Public OR Democracy OR Democratic). Full-text article search yields roughly 10x as many hits. 20051995

3. Elements of Democratic Deliberation Criteria for Evaluating Deliberation Analytic rigor of panels Learning basic issue information Examination of underlying values Consider range of alternatives Weighing pros/cons of measure Democratic discussion process Equality of opportunity to participate Comprehension of information Consideration of different views Mutual respect among citizens Writing/voting on Statement Informed decision making Non-coercive process

4. Research problems or agendas in deliberative democratic theory How can we assess: – the degree to which government agencies (and executive branches generally) deliberate democratically? – legislative deliberation, both on the floor and in committees? – the degree to which publics are included in the wider governance process? – the deliberative quality of public discourse more generally on a range of issues (and across nations)?

5. A sampling of analytic methods used in delib. dem. research Discourse Quality Index (justifications, etc.) Coding for analytic rigor (deliberation) and democratic social relations Argument repertoire/diversity Message homogeneity (talking points) Holistic codings of process quality

6. PInet research competition ideas Solicitation for developing an analytic method that lends itself to automatic coding, yet can withstand a validation test against more careful human coding approaches Competition announced through two main associations/networks: Natl. Comm. Assn. and the Intl. Comm. Assn.

7. Questions and Concerns The most feasible and reliable approaches to automatic coding may lack validity. The most valid content analytic approaches may not be feasible. Can we assemble a research team that can sustain the long-term investment of time and resources required to overcome the validity/feasibility problem?