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对高度复杂,多系统问题的参与式建模:平衡定性理解和定量问题的挑战和建议
Arielle R Deutsch1,2, Leah Frerichs3, Madeline Perry3
1Avera Research Institute, Avera Health, Sioux Falls, SD, USA.
概括
开发复杂的参与型模型需要对利益相关者进行仔细的参与,界限的定义,以及定性/定量整合. 应对这些挑战是创造可用于系统变革的可操作见解的关键.
科学领域:
- 系统科学 系统科学
- 参与式建模参与式建模
- 计算社会科学 计算社会科学
背景情况:
- 社区利益相关者参与增强了定性模型的开发.
- 参与式建模面临着高度复杂,多系统交互的挑战.
- 将定性模型转化为决策的定量模拟是困难的.
研究的目的:
- 突出开发高复杂度,参与型模型的实际挑战.
- 在系统动态项目中提出解决这些挑战的建议.
- 为研究可翻译的定性多系统模型提供基础.
主要方法:
- 一个正在进行的参与式建模项目的案例研究.
- 专注于系统动态工具,用于高度复杂的多系统问题.
- 确定利益相关者参与和模式整合的关键挑战.
主要成果:
- 确定了三个主要挑战:利益相关者参与,界限定义和定性/定量整合.
- 为应对这些具体挑战而提出的建议.
- 强调需要在复杂的参与式建模中采用最佳实践.
结论:
- 解决参与,边界和整合对于有效的参与建模至关重要.
- 需要进一步研究开发可翻译的定性多系统模型的方法.
- 改进的模型可以为系统变革的行动提供信息.
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