手法を比較

	Visioning Preferred Futures Workshop	Causal Layered Analysis
分野	Futures Foresight Studies	Futures Foresight Studies
系統	Process / pipeline	Process / pipeline
提唱年	2009	1998
提唱者	Hawai'i School / Millennium Project futures-visioning tradition	Sohail Inayatullah
種類	Normative, participatory backcasting pipeline toward a preferred future	Layered deconstruction-and-reconstruction pipeline for futures and problem analysis
原典	Glenn, J. C., & Gordon, T. J. (Eds.). (2009). Futures Research Methodology, Version 3.0. The Millennium Project. ISBN: 9780981894119	Inayatullah, S. (1998). Causal layered analysis: Poststructuralism as method. Futures, 30(8), 815-829.
別名	Preferred Futures Visioning, Visioning Workshop, Normative Futures Visioning, Aspirational Futures Method	CLA, Causal Layered Analysis Method, Inayatullah CLA, Layered Futures Analysis
関連	3	3
概要	A Visioning Preferred Futures Workshop is a normative, participatory futures method for articulating a shared image of the future a group wants to create, and then working backward from that image to identify the pathway and the present actions that would bring it about. Where exploratory methods ask what futures might happen, visioning asks what future ought to happen and how to get there. Documented as a core technique in the Millennium Project's Futures Research Methodology, it combines aspirational image-building with backcasting: participants first agree on a compelling preferred future grounded in their shared values, then trace the milestones backward from that future to the present, and finally commit to concrete first steps. The method's power lies in mobilizing a community around a positive, jointly owned vision rather than around forecasts or fears.	Causal layered analysis (CLA) is a critical futures method developed by Sohail Inayatullah and set out in his 1998 paper 'Causal layered analysis: Poststructuralism as method.' Rather than forecasting, its aim is to open up the space of possible futures by reading an issue at four levels of depth. The surface 'litany' of headlines and accepted trends sits atop systemic causes, which rest in turn on the worldviews and discourses that legitimate them, all anchored in deep myths and metaphors. By moving down through these layers to expose the assumptions and narratives beneath a problem — and then reconstructing upward from a transformed deep story — CLA produces futures that differ not merely in detail but in their underlying logic.