METHODS: We interviewed 25 key policy actors. We analysed the interviews using purposive text analysis (PTA). We developed individual then combined casual loop diagrams to generate a shared model representing the DR-NCD prevention policy-making system. Key variables/linkages identified from the literature were also included in the model. We validated the model in several steps including through stakeholder validation interviews.
RESULTS: We identified several inter-linked feedback processes related to political economy factors that may entrench different forms of corporate power (instrumental, structural, and discursive) in DR-NCD prevention policy-making in South Africa over time. We also identified a number of feedback processes that have the potential to limit corporate power in this setting.
CONCLUSIONS: Using complex system methods can be useful for more deeply understanding DR-NCD policy inertia. It is also useful for identifying potential leverage points within the system which may shift the existing power dynamics to facilitate greater political commitment for healthy, equitable, and sustainable food system transformation.
方法:我们采访了25个关键政策参与者。我们使用目的性文本分析(PTA)对访谈进行了分析。我们开发了个人,然后将临时循环图组合在一起,以生成代表DR-NCD预防政策制定系统的共享模型。从文献中确定的关键变量/联系也包括在模型中。我们通过几个步骤验证了模型,包括通过利益相关者验证访谈。
结果:我们确定了几个与政治经济因素相关的相互关联的反馈过程,这些过程可能会巩固不同形式的公司权力(工具,结构,和话语)随着时间的推移,在南非的DR-NCD预防政策制定中。我们还确定了一些反馈过程,这些反馈过程有可能在这种情况下限制企业的权力。
结论:使用复杂系统方法可以更深入地理解DR-NCD政策惯性。它也有助于识别系统内的潜在杠杆点,这些杠杆点可能会改变现有的权力动态,以促进更大的政治承诺,公平,和可持续的粮食系统转型。