Data from: Mitigating collision-caused bird mortality through message framing: Insights from residents' intentions for bird-safe windows
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https://datadryad.org/dataset/doi:10.5061/dryad.qbzkh18wd
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资源简介:
Efforts to change human behavior for the benefit of biodiversity often
rely on the dissemination of scientific information about biodiversity
loss to nonscientific publics. This approach to science communication,
known as the knowledge deficit model, is often insufficient for changing
behavior. Recent trends reveal a rise in the use of message framing as an
alternative method of communication. To address biodiversity loss caused
by bird-window collisions, we use experimental survey design to compare
the effect of deficit model messaging and four message frames (efficacy,
emotional, moral, normative) on residents' intentions to adopt
bird-safe windows, while accounting for other potentially influential
cognitive and contextual factors. Data from a sample of bird enthusiasts
(n = 2854) and the general public
(n = 2054) in the United States and Canada indicate
efficacy and emotional message frames were the most effective for bird
enthusiasts and the general public, respectively. Prior experience with
collisions, perceived impact of collision prevention, centrality of
birding, educational attainment, and mutualist wildlife value orientations
were also positively associated with respondents' intention to adopt
bird-safe windows. Normative message frames, age, identification as male,
residency in the U.S., and domination wildlife value orientations were
negatively associated with adoption intention. Beliefs about collision
prevention, centrality of birding, age, education, and wildlife value
orientations also had similar associations with respondents'
intention to encourage others to make their windows bird-safe. Results
provide important insights for the mitigation of collision-caused bird
mortality through evidence-based message framing, and the actions people
are willing to take on behalf of birds and biodiversity.
提供机构:
Dryad
创建时间:
2025-10-09



