Yes, strange question... and perhaps necessary in some contexts. Wether the only way to embrace a complex object of study (e.g. social impacts of a big project of infrastructure) coincide with the "unfaithfull" of a enterprise wich department of r+d only believe in "numbers" and "strict steps"... and perhaps some of "where's your model for a project like the mine?"... Could be a choice to construct "the best possible-model" for this kind of situations? For "legitimating our job?", and at the same time for "introducing a qualitative-methodology-is-reliable" axiom into som rigid and traditional scientific minds?"... Both? Some more?
Use Baysian statistics of multiple factors with qualitative strength will give you the appropriate model
The advantage is that additional factors can then be included or strengthened depending on future results or research
Hope that can help. See landscape logic program for an example from the un of Tasmania, google it
Barry
Thank you John. I'm looking at it and could be an useful tool. My point is even more qualitative. Understanding statements of stakeholders implies, for example, knowing their discourses, their social positions and versions of the project (e.g., a hidropower infrastructure, that affects to thousands people, in different communities along a river basin). The question would be how to reduce the complexity of discourses, social relations, power relations... Well, there's no prize without pain :-). It's our job.
The other subject to investigate is the concept of ecosystem services and ways thiese e quantified or t least part of an equation. If you can get a hold of the ok from the2011 AELI UK book on the subject of
ecosystem services in landscape ecology there of some examples of approaches to quantify societies needs for an area
Thank you so much John, but I can not understand the reference you give. Would you give me something more complete (no hurry)? Thanks again.
Within the world of scenario planning, this is one of the key challenges. How to link qualitative information derived from a broad variety of stakeholders with different worldviews, discourses, and power relations, with quantitative models. In my mind, "iteration" is the key word. So develop models while also acquiring qualitative data working with stakeholders. Qualitative information can then be quantified and used to apply models; and results of the models can be discussed with stakeholders. By going through this cycle a few times, consistency between qual and quan products (hopefully) increases. There are a variety of methods and tools that is being experimented with to work with stakeholders on products that are semi-quantitative or even quantitative to help bridging the gap between qual and quan. A few refs that might help you:
Kok, K. 2009. The potential of Fuzzy Cognitive Maps for semi-quantitative scenario development, with an example from Brazil. Global Environmental Change 19: 122-133
(I'm using this quick and dirty tool directly with stakeholders)
Alcamo, J. (Ed.), Environmental futures: the practice of environmental scenario analysis. Developments in Integrated Environmental Assessment – Volume 2. Elsevier, Amsterdam.
(Joseph Alcamo explains a framework, called Story-And-Simulation)
Giaoutzi and Sapio. Recent Developments in Foresight Methodologies. Springer Book.
(a number of excellent chapters on linking qual and quan scenarios)
Let me know if you have access to this. I can provide you with some PDFs if needed.
That is the point! These days my team and me are initiating the construction of a "standarized" methodology for social impact assessment, combining both kind of methodologies. Our early considerantions coincide with the ideas I can over-read in you RG pubs. profile.
Dear Babak,
to address your sub-question:
No, I've not used SSM, but it is very similar to the Fuzzy Cognitive Mapping that I have used many times. Key to both tools is to construct a Conceptual Model, that represents the views of the stakeholders involved in constructing it, rather than "reality" (if such a thing exists in human systems...).
What I like about FCMs, is that they can be termed semi-quantitative, as all relationships are given a strength between -1 and +1. This opens the possibility for iteration and creating a semi-dynamic output. This is a characteristic that many other conceptual modelling tools lack..
But in short: Yes, I've a similar method; and yes, I think it has a lot of potential!
Wops! Great level. I like this line. Kasper, great and clear papers (I'm reading them). Super-interesting focus, and very good effort to summarize qual ad quan information from reality. An economist, partner of mine, when I ask him too much about how his models respond to reality, he use to say (after a couple of beers...): "Oh, ok Andres, let me be... Don't let the reality to brake your model!" :-)
Thank you so much Alessandro. I looked for that reference... but difficult to reach in this economic crisis (near to 200€!!). Any suggestions about "grey literature" (journal articles)? Thanks again
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