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Scripts supporting policy uncertainty and alignment diagnostics related to short food supply chains

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DataCite Commons2026-04-08 更新2026-04-25 收录
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https://data.4tu.nl/datasets/fa7603c4-bc14-43e1-897e-697bc8e791fb/1
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资源简介:
Contains a Python script that implements a computational governance diagnostic framework for analysing policy documents related to Short Food Supply Chains (SFSCs), with a specific focus on South Africa. The research objective is to find (1) how conceptually focused or diffuse SFSC themes are in national policy domains, (2) which domains show strong or weak alignment with international food sustainability frameworks, and (3) what uncertainty-coherence patterns reveal about the integration of SFSC governance in South Africa. The method involves corpus curation; topic modelling using Latent Dirichlet Allocation (LDA); uncertainty quantification via Shannon entropy; cross-corpus alignment analysis using Jensen-Shannon Divergence (JSD) and Cosine Similarity; and policy alignment network construction. The dataset comprises the executable script (.ipynb) and a detailed README guide. No primary source policy documents are included; the script is designed to be run by users on their own collections of national and international policy PDFs. In any case, all documents used are freely available online
提供机构:
4TU.ResearchData
创建时间:
2026-04-08
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