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Abstract Science and innovation policy in the USA often frame publics as the beneficiaries of new technologies, but little research has yet engaged publics on their views of the innovation system (IS)—the combined efforts of government, industry, and universities to produce and promote new technologies. Based on a national public survey (n = 3,010), we identify three dimensions of public judgments about the IS with public policy implications: (1) US publics hold moderate confidence in the IS to produce benefits for them and to respond to public input; (2) they are slightly more critical of innovation-related environmental harm and the accrual of benefits to large corporations; and (3) they strongly support reforms to ensure safe, responsible, and affordable technological innovation. Multivariate regressions indicate variance of judgments by social location and worldviews, finding equity and justice aspects particularly salient in views on the IS. We discuss implications for innovation policy.
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Who Do You Think We Are? The Data Publics in Digital Government Policy
This study provides conceptual clarity on open data users by connecting an empirical analysis of policy documents to emerging theoretical research on data publics. Releasing files to the public for reuse is the primary objective of policy on open government data. Recent public sphere scholarship provides insights into who reuses data by defining a data public as people who actively construct narratives with openly available digital sources. A content analysis of United States federal policy documents identified the language used to represent people who might reuse data. An inductive qualitative analysis of mandated digital strategy reports generated a taxonomy that characterizes people mentioned in open data policy. In addition to the taxonomy, this research contributes a set of propositions to predict data reuse based on these characteristics. The results encourage further dialog between public sphere and digital government scholars to establish testable explanations about data publics.
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- Award ID(s):
- 1635449
- PAR ID:
- 10191197
- Date Published:
- Journal Name:
- Proceedings of the Hawaii International Conference on System Sciences
- ISSN:
- 0073-1129
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.24251/HICSS.2019.394
