ArticleAmbio2024
Identifying leverage points for sustainable nutrient policy integration in Canada.
Article in Ambio, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Authors and funding
3 authors.
Funding
Abstract
Addressing the 'wicked problem' of nutrient pollution requires coordinated policies spanning across diverse sectors and environmental systems. Using a case study of Canadian legislation, we apply semantic network analysis to identify thematic links across an inventory of 245 nutrient-related policies. Our analysis identifies twelve topics with unique types of connections across multiple facets of Canadian society. 'Hub' policies include broad environmental protection, land use planning, and climate-related legislation with close ties to multiple other topics. 'Bridge' policies create connections among otherwise disconnected topics in the network, representing opportunities to inform new policy proposals. Some legislation, such as food processing regulations, indirectly relates to nutrient use but could inform policy integration towards more coordinated and holistic nutrient management across the food system. A computational text network approach can be useful for addressing challenges in complex policy analysis, including by identifying unique entry points to guide more cross-cutting nutrient policy development.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.