Causal layered analysis

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Causal layered analysis (CLA) is one of several futures techniques used as a means to inquire into the causes of social phenomena and to generate a set of forecasts as to the future course of the phenomena.

Theory

As a theory, CLA seeks to integrate empiricist, interpretive, critical and action learning modes of knowing (loosely, science, social science, philosophy and mythology). As a method, its utility is not in predicting the future but in creating transformative spaces for the creation of alternative futures. It is also likely to be of use in developing more effective — deeper, inclusive, longer term — policy.

Causal layered analysis consists of four levels: the litany, social causes, discourse/world-view and myth/metaphor.

The first level is the litany – the official unquestioned view of reality.
The second level is the social causation level, the systemic perspective. The data of the litany is explained and questioned at this level.
The third level is the worldview/discourse. Deeper, unconsciously held ideological, worldview and discursive assumptions are unpacked at this level. The way in which different stakeholders construct the litany and system are also explored.
The fourth level is the myth-metaphor, the unconscious emotive dimensions of the issue. The challenge is to conduct research that moves up and down these layers of analysis and thus is inclusive of different ways of knowing. Doing so allows for the creation of authentic alternative futures and integrated transformation. CLA begins and ends by questioning the future.

Advantages

CLA has these advantages:

Expands the range and richness of scenarios (the CLA categories can be used in the incasting phase);
When used in a workshop setting, it leads to the inclusion of different ways of knowing among participants;
It appeals to and can be used by a wider range of individuals as it incorporates non-textual and poetic/artistic expression in the futures process;
CLA layers participant's positions (conflicting and harmonious ones);
It moves the debate/discussion beyond the superficial and obvious to the deeper and marginal;
It allows for a range of transformative actions;
CLA leads to policy actions that can be informed by alternative layers of analysis; and
CLA reinstates the vertical in social analysis, that is, from postmodern relativism to global ethics.

Embedded in the emerging discourse of futures studies, causal layered analysis (CLA) draws largely from poststructuralism, macrohistory, and postcolonial multicultural theory. It seeks to move beyond the superficiality of conventional social science research and forecasting methods insofar as these methods are often unable to unpack discourses — worldviews and ideologies — not to mention archetypes, myths, and metaphors.

Causal layered analysis is concerned less with predicting a particular future and more with opening up the present and past to create alternative futures. It focuses less on the horizontal spatiality of futures and more on the vertical dimension of futures studies, of layers of analysis. Causal layered analysis opens up space for the articulation of constitutive discourses, which can then be shaped as scenarios. In essence, CLA is a search for integration in methodology, seeking to combine differing research traditions.

These traditions are in flux: in the social sciences generally and futures studies specifically. Futures studies has decisively moved from ontological concerns about the nature of the predicability of the universe to epistemological concerns about the knowledge interests in varied truth claims about the future.

This has led futures studies from being focused on empirical/prediction modes to interpretation and ethnography (the meanings we give to data). And the field’s conceptual evolution has not stopped there. More recently, futures methodologies have been influenced by the poststructural thrust, with concerns for not what is being forecasted but what is missing from particular forecasts and images of the future. This is the layered approach to reality.

At the same time, the limits of instrumental rationality and strategic consciousness have become accepted, largely because of critiques of rationality by scholars associated with the environmental movement, the feminist movement, and spiritual movements — the new post-normal sciences — among others. Moreover, while globalisation has not suddenly developed a soft heart, the agenda now includes how we know the world and how these knowings are complicit in the disasters around us.

Within the CLA framework, the move to post-structuralism, is not at the expense of data–orientation or meaning–oriented research and activism. Indeed, data is seen in the context of meanings, within the context of epistemes (or knowledge parameters that structure meanings; for example, class, gender, the interstate system), and myths and metaphors that organise the deep beliefs, the traumas and transcendence that over time define identity — what it means to mean and to be.

CLA does not argue for excluding the top level of the iceberg for bottom–of–the–sea analysis; rather, all levels are required and needed for fulfilling — valid and transformative — research. Moreover, in this loop of data–meaning–episteme–myth, reconstruction is not lost. Action is embedded in epistemology.

With the CLA framework, the politics of epistemology is considered part of the research process. Politics is acknowledged and self-interest disclosed. Of course, not all self-interest can be disclosed since individuals operate from epistemes that are often outside of our knowing efforts. Indeed, epistemes shapes what we can and cannot know. While eclectic and layered approaches hope to capture some of the unknowns, by definition, the unknown remains mysterious. Acknowledging the unknown is central to futures research. This does not mean that the future cannot be precisely predicted, but rather that the unknown creeps into any research, as does the subjective. Moreover, the unknown is expressed in different ways and different ways of knowing are required to have access to it. Freeing methodology from politics is a never–ending task; however, within the CLA framework this is accomplished not by controlling for these variables but by layering them.

External links

Articles on CLA
An article by Sohail Inayatullah describing Causal Layered Analysis: "Causal Layered Analysis: poststructuralism as method"
A description of the methodology
An article by Sohail Inayatullah describing Causal layered analysis
Case studies of causal layered analysis at Journal of Futures Studies. For example, an article by Rowena Morrow: "What is the debate about paid maternity leave really about: using CLA to delve under the surface"

Causal layered analysis

Theory

Advantages

See also

External links

Further reading