Soft systems thinking seems squishy

Georgina Cundill from Rhodes University in South Africa and some co-authors have an essay in the latest Conservation Biology entitled "Soft Systems Thinking and Social Learning for Adaptive Management". I've gotten interested in the literature on social learning as a result of some recent interactions with colleagues in political science, but I'd never heard of soft systems thinking before. The motivation for the paper is simple: "It is now generally accepted that social and political processes can determine whether management initiatives succeed irrespective of the quality of the science that supports them ..." and so "hard systems thinking" (which is what I do) will fail. They define AM by reference to Carl Walter's seminal book, but by assuming that AM is a monolithic concept they muddy the waters considerably. For example, when they assert that

Adaptive management often starts with a conceptual model or set of objectives or hypotheses to be tested, and then experimentation is used to validate, refute, and, ultimately, modify and refine the model and to make informed trade-offs among goals that may conflict ...

they are largely referring to actions that define the Experimental-Resilience school, but slip in decision theoretic ideas of objectives and trade-offs that are are rarely, if ever, the focus of Experimental Resilience approaches. In contrast, their definition of "hard systems thinking" as

decision making in pursuit of goals or objectives. Here we refer to this approach as objective-based management. This approach is evident in the step-by-step process of adaptive management
that begins with the identification of objectives.

which is the basis for Decision Theoretic approaches to AM.
So what does shifting to soft systems thinking add? I struggled to find a clear definition to quote - but the idea seems to be that a soft systems approach includes the people as part of the system. Wow, that sounds like a socio-ecological system! As a result, the system cannot be engineered towards an optimum, because the purpose of the system is an emergent property of the interactions among the people involved.
The idea of social learning is less squishy - they define it as

the collective action and reflection that takes place among both individuals and groups
when they work to understand the relations between social and ecological systems; it is conceptualized as a process of transformative social change in which participants critically question and potentially discard existing norms, values, institutions, and interests to pursue actions that are desirable to them. 

So if you're talking about a socio-ecological system, then social learning is the process by which the social components of the system respond to new information.


They then describe a new methodology for AM derived from these processes. The methodology consists of 4 assumptions and 4 actions. Their assumptions are so ambiguous as to be almost tautologically true of any socio-ecological system, so I won't repeat them. So what actions do they recommend?

1. Situate and engage rather than defining objectives, figure out what the problem is from as many different perspectives as possible, and determine who is interested in the problem. 
2. Raise awareness and encourage Enquiry and Deconstruction clarify and refine different frames of reference among the stakeholders, leading to the development of shared frames of reference.
3. Take collaborative actions based on co-created frames of reference, and that are agreed upon by all the actors.
4. Reflect on learning to continue the process of modifying frames of reference of all the actors. 

They go on to outline challenges to implementation, which include the observation that all of this is context specific (making general procedural recommendations impossible), and that conservation scientists lack any kind of training in the skill sets relevant to these sorts of social processes. 

It seems to me that the only real difference is whether one is taking a proscriptive stance on decision making versus a descriptive stance. Hard systems approaches are proscriptive - they describe what you should do, in which order, and provide recipes for carrying out each step. In contrast, this soft systems/social learning approach is describing what actually happens when a group of actors tries to manage a resource. 

My personal view is that fruitful progress involves collaboration between hard and soft systems thinking. Without understanding the social dynamics, hard systems approaches risk spending resources (people's time, mostly) without gain, and soft systems approaches are, well, too soft to provide useful guidance in all circumstances. There are situations where it is OK to be as hard as a rock, and situations where the best strategy is to be soft and squishy. What we need are frameworks to help us divine the appropriate mix of strategies in any particular situation.