How to measure deliberative success?

Discourse Quality Index u.a. / No good solutions to that question yet. cf. Gary S. Schaal und Claudia Ritzi, “Empirische Deliberationsforschung.”see also:Simon Niemeyer, “Deliberation and the Public Sphere: Macro lessons from Minipublics.”: 7.

cf Walter und Krabbe 1995. /

(Walton and Krabbe 1995). Effective deliberation requires that:
• All important issues are considered
• The broadest possible range of high-quality solution ideas are identified
• The strongest arguments for and against each idea are captured
• People can distinguish good from bad arguments
• Individual select solutions rationally, i.e. they consider all the important issues and ideas, and make selections that are consistent with the arguments they most trust
• The aggregate results fairly represent the “wisdom of the people"


By far the most commonly used technologies, including wikis like wikipedia, media sharing sites like youtube facebook and flickr, open source efforts such as Linux Mozilla and Apache, idea markets such as innocentive, and web forums such as digg and Slashdot, fall into the sharing category. While such tools have been remarkably successful at enabling a global explosion of idea and knowledge sharing, they face serious shortcomings from the standpoint of enabling large-scale deliberation around complex and controversial topics (Sunstein 2006) (also see http://en.wikipedia.org/wiki/Criticism_of_Wikipedia):low signal-to-noise ratio. The content captured by sharing tools is notorious for being voluminous and highly repetitive. This is a self-reinforcing phenomenon: since it can be difficult to find out whether an idea has already been proposed in a large existing corpus, it’s more likely that minor variants will be posted again and again by different people. People may also, conversely, decide not to enter an idea, assuming it already appears somewhere.
This low signal-to-noise ratio makes it difficult to uncover the novel ideas that inspire people to generate creative new ideas of their own.
• unsystematic coverage caused by bottom-up volunteer-based contributions. It’s hard to tell what areas are covered in detail and which are not, since there is no compact overview available and no one ‘in charge’. There is, as a result, no guarantee that the key issues, best ideas, and strongest arguments have been systematically identified.
• balkanization: Users of sharing systems often tend to self-assemble into groups that share the same opinions - there is remarkably little cross-referencing, for example, between liberal and conservative web blogs and forums - so they tend to see only a subset of the issues, ideas, and arguments potentially relevant to a problem.
• dysfunctional argumentation: Sharing systems do not inherently encourage or enforce any standards concerning what constitutes valid argumentation, so postings are often bias- rather than evidence- or logic-based, and spurious argumentation is common. Users with divergent opinions often engage in forum “flame wars” (wherein discussions degrade into repetitive arguments and ad hominem attacks) and wiki “edit wars” (where users attempt to “win” by removing each other’s perspectives from an article). Such phenomena have forced the shutdown of many forums as well as the locking of many wikipedia pages (so they can not be
edited by the public). All these effects seriously degrade the community’s ability to fully consider a problem.
• hidden consensus: Sharing tools do not provide any explicit means for identifying a group’s consensus on a given issue.

1. Mark Klein, “The MIT Collaboratorium: Enabling Effective Large-Scale Deliberation for Complex Problems” SSRN eLibrary (Dezember 2007), http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1085295.

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