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Informing Public Engagement Strategies to Motivate the Public to Protect the Great Lakes: Lessons learned from the 2018 Great Lakes Basin Binational Poll

机译:通知公众参与策略激励公众保护大湖泊:从2018年大湖流域投票中吸取的经验教训

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Engaging the public in protecting water resources is a critical yet challenging task. A wealth of social science studies has identified psychological predictors for individual pro-environmental behaviors. These predictors can guide communication in public engagement and inform the allocation of engagement efforts. However, a thorny challenge is to select influential factors among many candidates. This paper addresses this challenge by using social science research to guide the development of strategies to motivate the public to protect the North American Great Lakes. We considered a variable selection technique, the LASSO regression, in the post-hoc analysis of the International Joint Commission's 2018 Binational Great Lakes Binational Poll data. The poll surveyed 4250 Canadian and U.S. residents of the Great Lakes basin. We fit LASSO logistic models to predict respondents' intentions to take three public actions to protect the Great Lakes, including contacting public officials, attending public meetings, and engaging in online forums and groups. The models included 41 predictors encompassing demographic characteristics as well as respondents' awareness, beliefs, and values that are pertinent to Great Lakes policy development and management. Results revealed eight variables that consistently predicted the three public actions, including indigenous status, political ideology, impacts of the specific policy issues of nuclear wastes, policy awareness and interests, and the Great Lakes values for personal benefits and wildlife. Based on these findings, we recommend strategies to motivate the public to take public actions to protect the Great Lakes.
机译:从事公众保护水资源是一个关键而挑战的任务。一项丰富的社会科学研究已经确定了个别亲环境行为的心理预测因子。这些预测因素可以指导公共参与的沟通,并告知分配参与措施。然而,棘手的挑战是在许多候选人中选择有影响力的因素。本文通过使用社会科学研究来指导策略的发展来解决这一挑战,以激励公众保护北美大湖泊。我们考虑了一个可变选择技术,套索回归,在国际联合委员会2018年二十八届巨大湖泊锦民民民族民意调查数据的分析中。民意调查调查了4250个加拿大和美国居民的大湖盆地。我们适合套索物流模型,以预测受访者的意图采取三个公共行动来保护大湖泊,包括联系公职人员,参加公开会议,并从事在线论坛和团体。该模型包括41个预测因子,包括人口统计特征以及与大湖政策开发和管理相关的受访者的意识,信仰和价值观。结果揭示了八个变量,持续预测了三个公共行动,包括土着地位,政治意识形态,核废物的具体政策问题,政策意识和利益的特定政策问题以及个人福利和野生动物的大湖泊价值。根据这些调查结果,我们建议策略激励公众采取公共行动以保护大湖泊。

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