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Chapter 7.Science Issues for the Attention of Policy Makers7.1. IntroductionThe identification of new and emerging issues, drawing onscientific evidence, assessments and projections, is afunction of the science-policy interface (see Chapter 1). Inthis context, this chapter reports on the process and resultsfrom an experiment to crowd-source briefs from interestedscientific communities around the world. This initiative wasundertaken in the context of identifying “emerging issues”from a science-based perspective.The categorization of an issue as “emerging” involves adegree of subjective judgment, as emphasized, e.g., in theUNEP Foresight process 2012. 540 An issue can also beunderstood as emerging where the scientific communityconsiders it important, but the policy community has notgiven it “adequate” attention. Others argue that an issuebecomes “emerging” as soon as there scientific confidencein causality is established. 541 It must be clear that these arebroad generalizations; some issues have been squarely onthe policy agenda – climate change for instance – for a longtime, but with attention arguably failing to translate intoaction commensurate with the scale of the problem. Theinherently subjective process of identifying “emergingissues” can be guided by criteria, e.g., those used in theUNEP Foresight exercise. In an inter-dependent world,what at first appear to be local and isolated problems maypotentially be of global significance.Table 7-1. UNEP foresight criteria for “emerging issues”Indicative criteriaIllustrative issueGlobal significance - is critical to achievingsustainable development in many parts of the worldAffects one or more of the dimensions ofsustainable developmentEvidence-based, including scientific and traditionalsources of knowledgeNewness - the result of new knowledgeSource: Adapted from UNEP Foresight 2012. 540Climate changeDisasterreductionBiotechnology,GMOsOcean acidificationA range of approaches can be applied to identify a set ofemerging issues; a common way is expert consensus, usingcriteria to collect an initial list of issues, which is thenwhittled down in the course of discussions among experts.The involvement of experts tends to enhance the credibilityof the process. 542 Criteria are explicit, and the process ofselection and elimination of issues can be transparentlyrecorded and justified. The overall exercise can becharacterized as systematic. However, while observers canscrutinise the process, initial choices about the framing andrisk131articulation of criteria, as well as the selection of experts,may significantly affect what issues are identified as“emerging”. Related to this, the perceived legitimacy ofsuch exercises will depend on the extent to which theprocess is perceived as unbiased and fair in the treatmentof views. These weaknesses may be overcome bycombining the structured process with crowd-sourcing.By contrast, the “crowd-sourced” approach adopted for theGSDR and described below lacks the systematic characterof more formal exercises designed to identify emergingissues. Lacking the pedigree of formal assessmentexercises, credibility is more difficult to assess, but can bejudged from, e.g., the degree to which findings aregrounded in the peer-reviewed literature. Because theopen call contained only very minimal criteria, very fewissues were foreclosed from the beginning. In a sense theapproach can be compared to the first, scoping stage of anexpert-led process, when the “raw” list of issues iscompiled. But for the present report the process of scopingwas decentralized with expert contributors from diversedisciplines and a range of countries. As a result, policymakersgain access to a bottom-up, largely unfilteredscience perspective, with the freedom to judge the policyrelevanceof the issues identified. Many inputs werereceived from younger scientists and scientists fromdeveloping countries who previously were not typicallyinvolved in UN-related activities and debates.The result is a wealth of information that scientists wouldlike policy makers to consider in their deliberations at theUnited Nations, in particular relation to the mandate of theHigh-level Political Forum on Sustainable Development(HLPF) to strengthen the science-policy interface. However,it must be emphasized that the crowd-sourcing exercise ispresented as a complement to more formal assessmentexercises in the context of the science-policy interface. Thisis in keeping with one of the overall objectives of the GSDRto feature a wide range of perspective from multiplechannels.The present chapter also presents selected highlights fromscientific journals on sustainability science and on big dataapplications for sustainable development. It reviewsexisting mechanisms in the UN system to identify“emerging issues” and provides empirical data on thetypical time-lags between environmental science andpolicy. It concludes with a number of issues forconsideration by the HLPF.