In recent years, the Knight News Challenge has emerged as one of the most important forums for stimulating innovation in digital journalism, and as a salient marker of the Knight Foundation's influence in the field. Yet, the scholarly literature has yet to unpack this contest: its design and execution; the applicants it attracts and the winners it funds; and the normative aims about the future of journalism that may be revealed in this process. This paper addresses that by examining content analysis data for nearly 5,000 applications to the Knight News Challenge, exploring the distinguishing features of applicants, finalists, and winners-and how particular features are associated with one's proposal advancing in the contest. A logistic regression suggests that, among other factors, those applications that advanced to the finalist and winner stages tended to include forms of participation (e.g., "user manipulation" and "crowdsourcing") as well as other features (e.g., software development) not typically associated with journalism. These findings are placed in the context of the Knight Foundation's broader efforts to shape journalism innovation.

1. The Knight News Challenge: How it works, what succeeds, and why that matters for the shaping of journalism innovation Seth C. Lewis School of Journalism & Mass Communication University of Minnesota – Twin Cities @SethCLewis International Symposium on Online Journalism; Austin, TX; April 2, 2011

2. the contest … and its content

3. RQ1: relationship between proposal features and advancing?

4. RQ2: participatory media features and advancing in the contest?

5. methods

6. profile of ‘08-09 proposals Type Number Percentage Applicants 4,369 89% Finalists 535 11% Winners 25 less than 1% Total 4,929

7. profile of ‘08-09 proposals - 54% organizations (vs. individuals) - 2% newspapers - 64% were not media/journalists

8. major predictors of advancing (or not)

9. major predictors of advancing (or not)

10. major predictors of advancing (or not)

11. major predictors of advancing (or not)

12. major predictors of advancing (or not)

13. major predictors of advancing (or not)

14. takeaways: news, info, tech participation opening boundaries

15. thanks. @SethCLewis