Scaling science

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dc.contributor.author Gargani, John
dc.contributor.author McLean, Robert
dc.date.accessioned 2017-10-30T12:47:49Z
dc.date.available 2017-10-30T12:47:49Z
dc.date.issued 2017
dc.identifier.citation Gargani, J., & McLean, R. (2017). Scaling science. Stanford Social Innovation Review, 15(4), 34-39. en
dc.identifier.issn 1542-7099
dc.identifier.uri http://hdl.handle.net/10625/56727
dc.description.abstract The traditional approach to delivering interventions at scale starts with the assumptions of reliable solutions in favorable contexts. In the case of the Ebola outbreak in 2014, these assumptions were useless. Like the Ebola crisis, many of the most pressing problems are ones that have been unsolvable perhaps for decades. This paper focuses on the mechanisms of scaling up which take into account issues of uncertainty. As an alternative to industrial scaling, a more comprehensive approach focuses on the additional objective of the public good. Scaling science is built on these four guiding principles: moral justification, inclusive coordination, optimal scale, and dynamic evaluation. en
dc.format.mimetype application/pdf
dc.language.iso en
dc.publisher Stanford University en
dc.subject SCIENCE en
dc.subject INNOVATION en
dc.subject SOCIAL PROGRESS en
dc.subject GLOBAL SOUTH en
dc.subject PUBLIC GOOD en
dc.subject SCALING UP en
dc.subject THEORY OF CHANGE en
dc.subject IMPACT ASSESSMENT en
dc.subject PROGRAMME PLANNING en
dc.subject INNOVATION SYSTEMS en
dc.subject EBOLA OUTBREAK en
dc.title Scaling science en
dc.type Journal Article (peer-reviewed) en
idrc.copyright.holder Leland Stanford Jr. University
idrc.copyright.oareleasedocrecordsserverdocnumber IC11-383107257-190
idrc.dspace.access Open Access en
idrc.rims.adhocgroup IDRC SUPPORTED en
dc.relation.journal Stanford Social Innovation Review
idrc.recordsserver.bcsnumber IC06-142367426-309


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