Hughes Caitlin E
Department of Criminology, The University of Melbourne, Victoria, Australia.
Drug Alcohol Rev. 2007 Jul;26(4):363-8. doi: 10.1080/09595230701373859.
Evidence-based policy is promoted as the ideal in drug policy, yet public policy theorists suggest that policy-based evidence may be a more fitting analogy, where evidence is used selectively to support a predetermined policy direction. The following paper assesses the resonance of this notion to the development of the Illicit Drug Diversion Initiative (IDDI), an apparently pragmatic reform adopted in Australia in 1999 through the Federal Coalition 'Tough on Drugs' strategy. It utilises interviews with key informants from the Australian drug policy arena conducted in 2005 to assess the role of evidence in the design and implementation of the IDDI.
The current paper shows that while policy-makers were generally supportive of the IDDI and viewed drug diversion as a more pragmatic response to drug users, they contend that implementation has suffered through a selective and variable emphasis upon evidence. Most notably, the IDDI is not premised upon best-practice objectives of reducing harm from drug use, but instead on 'Tough on Drugs' objectives of reducing drug use and crime.
This paper contends that policy-based evidence may facilitate the adoption of pragmatic reforms, but reduce the capacity for effective reform. It therefore has both functional and dysfunctional elements. The paper concludes that greater attention is needed to understanding how to mesh political and pragmatic objectives, and hence to maximise the benefits from policy-based evidence.
循证政策被推崇为毒品政策的理想模式,但公共政策理论家认为,基于政策的证据可能是一个更恰当的类比,即证据被有选择地用于支持预先确定的政策方向。以下论文评估了这一概念与非法药物转移倡议(IDDI)发展的共鸣,该倡议是澳大利亚于1999年通过联邦联盟“对毒品强硬”战略采用的一项明显务实的改革。它利用2005年对澳大利亚毒品政策领域关键信息提供者的访谈,来评估证据在IDDI设计和实施中的作用。
本文表明,虽然政策制定者普遍支持IDDI,并将药物转移视为对吸毒者更务实的应对措施,但他们认为,由于对证据的选择性和可变强调,实施受到了影响。最值得注意的是,IDDI并非基于减少吸毒危害的最佳实践目标,而是基于“对毒品强硬”的减少吸毒和犯罪目标。
本文认为,基于政策的证据可能有助于采用务实的改革,但会降低有效改革的能力。因此,它既有功能性要素,也有功能失调性要素。本文得出结论,需要更加关注如何协调政治目标和务实目标,从而最大限度地从基于政策的证据中获益。