Governments and social benefit organisations are expected to consider evidence in decision-making. In development and sustainability, evidence spans disciplines and methodological traditions and is often inconclusive. Graphical models are widely promoted to organize interdisciplinary evidence and improve decision-making by considering mediating variables. However, the reproducibility, objectivity and benefits for decision-making of graphical models have not been studied. We evaluate these considerations in the setting of energy services in the developing world, a contemporary development and sustainability imperative. We develop a database of relevant causal relations (331 concepts, 1355 relationships) asserted in the literature (561 peer-reviewed articles). We demonstrate that high-level relationships of interest to practitioners feature less consistent evidence than the causal relationships that underpin them, supporting increased use of problem decomposition through graphical modelling approaches. However, adding such detail increases complexity exponentially, introducing a hazard of overparameterization if evidence is not available to match the level of mechanistic detail.

预计政府和社会福利组织将在决策中考虑证据。在发展和可持续性方面，证据跨越学科和方法论传统，而且往往没有定论。图形模型得到广泛推广，以通过考虑中介变量来组织跨学科证据并改善决策。但是，尚未研究图形模型决策的可再现性，客观性和益处。我们在发展中世界的能源服务设置中评估这些考虑因素，这是当代发展和可持续性的当务之急。我们建立了一个相关的因果关系数据库（331个概念，1355个关系），这些数据库在文献（561篇同行评议的文章）中都得到了肯定。我们证明，从业者感兴趣的高级关系比支持他们的因果关系具有更少的一致性证据，从而支持通过图形建模方法增加问题分解的使用。但是，添加此类详细信息会成倍地增加复杂性，如果没有证据可以匹配机械详细信息的级别，则会带来过度参数化的危险。