Event Title

Science During Challenging Times: Theory, Methods, and Case Studies

Location

Library, Carnegie Institution for Science

Event Website

http://ipsonet.org/web/page/512/sectionid/375/pagelevel/2/interior.asp

Start Date

4-12-2023 1:00 PM

End Date

4-12-2023 2:00 PM

Description

Chair: Rex Kallembach, Policy Studies Organization

Abstract: Science and innovation policies (SIPs) aim at mobilizing knowledge in support of a wide range of societal aspirations and values. However, analytical tools and models for the assessment of SIPs focus predominantly on economic values. Analytical tools for assessing social impacts of science tend to be anchored in microeconomics (e.g. benefit-cost analysis). The assumptions upon which economics of innovation models and attendant tools are based inevitably affect SIP assessments and choices especially for policies of resource allocation and priorities. Nearly all observers, including economists, recognize that some social values are not well accounted for by economic models and measures. The influence of economic models in SIP is in part explained by limited progress in developing ways to conceptualize those science- and innovation-related values not easily expressed in monetary terms. Our research has been designed to further develop a public-values-based model for SIP. At the core of our work are two fundamental questions: What are the public values that justify particular SIPs, and what is the capacity of a given SIP to yield outcomes that support and advance those values? Our research has begun to yield better operationalization of these questions and to apply them to the development of a SIP decision model using a method that we call Public Value Mapping (PVM). Core assumptions of PVM are:
(1) that it is possible to identify public values, including ones not well captured by economic constructs;
(2) just as one can assess market failure, “public value failure” occurs when neither the market nor the public sector provides goods and services required to achieve designated public values; and
(3) innovation can be characterized not only in terms of contributions to economic growth and productivity but also in terms of public values achieved. PVM has many applications in support of science policy making, most notable when used in conjunction with public sector research and development policy analysis and evaluation. PVM goes beyond typical R&D evaluation to analyze and anticipate social impacts. To that end it can be useful to scholars and policy makers alike by expanding means and opportunities for considering broad research impacts.

Import Event to Google Calendar

 
Dec 4th, 1:00 PM Dec 4th, 2:00 PM

Science During Challenging Times: Theory, Methods, and Case Studies

Library, Carnegie Institution for Science

Chair: Rex Kallembach, Policy Studies Organization

Abstract: Science and innovation policies (SIPs) aim at mobilizing knowledge in support of a wide range of societal aspirations and values. However, analytical tools and models for the assessment of SIPs focus predominantly on economic values. Analytical tools for assessing social impacts of science tend to be anchored in microeconomics (e.g. benefit-cost analysis). The assumptions upon which economics of innovation models and attendant tools are based inevitably affect SIP assessments and choices especially for policies of resource allocation and priorities. Nearly all observers, including economists, recognize that some social values are not well accounted for by economic models and measures. The influence of economic models in SIP is in part explained by limited progress in developing ways to conceptualize those science- and innovation-related values not easily expressed in monetary terms. Our research has been designed to further develop a public-values-based model for SIP. At the core of our work are two fundamental questions: What are the public values that justify particular SIPs, and what is the capacity of a given SIP to yield outcomes that support and advance those values? Our research has begun to yield better operationalization of these questions and to apply them to the development of a SIP decision model using a method that we call Public Value Mapping (PVM). Core assumptions of PVM are:
(1) that it is possible to identify public values, including ones not well captured by economic constructs;
(2) just as one can assess market failure, “public value failure” occurs when neither the market nor the public sector provides goods and services required to achieve designated public values; and
(3) innovation can be characterized not only in terms of contributions to economic growth and productivity but also in terms of public values achieved. PVM has many applications in support of science policy making, most notable when used in conjunction with public sector research and development policy analysis and evaluation. PVM goes beyond typical R&D evaluation to analyze and anticipate social impacts. To that end it can be useful to scholars and policy makers alike by expanding means and opportunities for considering broad research impacts.

http://www.psocommons.org/dupont_summit/2009/schedule/4