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Abstracts (PDF file, 1.8MB) - Society for Risk Analysis

Abstracts (PDF file, 1.8MB) - Society for Risk Analysis

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SRA 2013 Annual Meeting <strong>Abstracts</strong><br />

P.59 Henning, CC*; Overton, AJ; Marin, K; Cleland, JC; Turley,<br />

AT; ICF International; cara.henning@icfi.com<br />

DRAGON: A Single <strong>Risk</strong> Assessment Database to Promote<br />

Transparency and Data Sharing<br />

With the availability of large volumes of data <strong>for</strong> risk<br />

assessment and a greater emphasis on consistency and<br />

transparency in federal agencies, data management and data<br />

sharing are of keen interest <strong>for</strong> risk assessors. The DRAGON<br />

tool is a database that stores risk assessment data and allows<br />

nimble management of the overall assessment process. Within<br />

DRAGON, the risk assessors can implement systematic review<br />

of the literature, manage the assessment of the quality of key<br />

studies and store related decisions, manage the data entry<br />

process, per<strong>for</strong>m dose-response modeling, and rapidly generate<br />

reports in a variety of <strong>for</strong>mats. The database itself has a unified<br />

structure that allows data-sharing across agencies and risk<br />

assessors with similar interests in a given chemical. Data-entry<br />

<strong>for</strong>ms, reports, and assessment decision logic can be tailored<br />

<strong>for</strong> each agency, though, to meet the different internal<br />

priorities and needs. Included in the database is an evolving<br />

health outcome standard vocabulary that can be crosswalked to<br />

any other vocabulary if needed. The vocabulary is based on a<br />

system-based classification <strong>for</strong> each endpoint. Specific<br />

endpoints can also be mapped to custom categories <strong>for</strong> each<br />

assessment as desired. DRAGON also provides a framework <strong>for</strong><br />

coordinating the work of multiple people working on<br />

assessments of chemicals with large databases to improve<br />

consistency and to facilitate quality assurance procedures.<br />

M3-F.2 Henry, AD; Dietz, T*; University of Arizona;<br />

adhenry@email.arizona.edu<br />

Co-Evolution of Beliefs and Networks in Environmental<br />

<strong>Risk</strong> Policy: An Advocacy Coalition Framework Approach<br />

Effectively managing issues of environmental risk requires<br />

collaboration within policy networks. Within the environmental<br />

policy process, networks of in<strong>for</strong>mation sharing, resource<br />

exchange, and other <strong>for</strong>ms of interaction allow organizations to<br />

synthesize in<strong>for</strong>mation and work towards shared goals.<br />

Ultimately, this allows policy actors to collectively learn how to<br />

deal with complex, uncertain, and emerging risks. Despite the<br />

importance of policy networks, however, the <strong>for</strong>ces that shape<br />

these structures — and possible interventions to promote more<br />

effective networks — are not well understood. According to the<br />

Advocacy Coalition Framework, the dynamics of policy network<br />

<strong>for</strong>mation lead to structures exhibiting belief-oriented<br />

segregation—that is, a high correspondence between shared<br />

policy beliefs and voluntary collaborative relationships. These<br />

structures may be produced through at least two pathways:<br />

belief homophily, where actors actively seek out connections<br />

with others sharing their belief system, and organizational<br />

learning, where policy beliefs diffuse through collaborative ties<br />

between organizations involved in risk policy. The<br />

cross-sectional design of many policy network studies precludes<br />

an explicit examination of these potentially complementary<br />

<strong>for</strong>ces. This paper explicitly examines these dynamics using a<br />

reanalysis of data on policy beliefs and networking in U.S.<br />

environmental risk policy across two time periods, 1984 and<br />

2000 (N = 223). Results indicate strong homophily effects, but<br />

relatively weak learning effects, in the evolution of this policy<br />

network. This research helps pave the way <strong>for</strong> additional<br />

research on the dynamics that share policy networks and<br />

beliefs, and also helps to clarify the differences between<br />

individual versus organizational contributions to policy network<br />

evolution.<br />

M4-B.6 Henry, SH; Aungst, J*; Castoldi, AF; Rhomberg, L;<br />

Butterworth, J; Retired Food and Drug Administration, Food<br />

and Drug Admin., European Food Safety Authority, Gradient<br />

Corp., Science journalist/investigative reporter;<br />

sarahalehenry10@yahoo.com<br />

Panel Discussion <strong>for</strong> A new look at the toxicity of<br />

bisphenol A and public health policy<br />

This panel discussion moderated by Sara Henry and Jason<br />

Aungst will allow presenters to interact with each other and<br />

then with the audience on the symposium topic of the toxicity of<br />

bisphenol and public health policy.<br />

M4-B.5 Henry, SH; Aungst, J; Castoldi, AF; Rhomberg, L;<br />

Butterworth, T; Fitzpatrick, J*; Retired Food and Drug Admin.,<br />

Food and Drug Admin., European Food Safety Authority,<br />

Gradient Corp., Science journalist/investigative reporter,;<br />

sarahalehenry10@yahoo.com<br />

A new look at the toxicity of bisphenol A and public<br />

health policy making<br />

A question and answer session with the presenters of this<br />

symposium and the audience will follow the panel discussion.<br />

Session will be moderated by Sara Henry and Julie Fitzpatrick<br />

December 8-11, 2013 - Baltimore, MD

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