There are two quite different ways of representing theories of change – of the kind that might be useful when planning and monitoring development programmes of one kind or another.
The first kind is seen in representational devices such as the Logical Framework, Logic Models and boxes-and-arrows type diagrams. These differentiate events according to their location at different points over time, taking place between the initial provision of funding, its allocation and use and then it's subsequent effects and final impacts. These are temporal models.
The second kind, seen much less often, are seen in the analyses generated by Qualitative Comparative Analysis (QCA) and simple machine learning methods known as Decision Trees or Classifiers. Here the theory is in the form of multiple configurations of different attributes that are associated with desired outcome, and its absence. Those attributes may be of the intervention and/or its context. The defining feature of this approach is the focus on cases and differences between cases, rather than different points or periods in time. These cases are often geographical entities, or groups or persons, which have some persistence over time. They are effectively atemporal models.
Each of these approaches have their own merits. Theory of change which describes the sequence of expected events over time and how they relate to each other is useful for planning, monitoring and evaluation purposes. But it runs the risk of assuming a homogeneity of effects across all locations where it is is implemented. On the other hand, a QCA-type configurational approach helps us identify diversity in contexts and implementations, and its consequences. But it may not have any immediate management consequences, about what needs to be done when.
One of my current interests is exploring the possibility of combining these two approaches, such that we have theories of change that differentiate those events over time, while also differentiating cases across space where those events may or may not be happening.
One paper which I've just been told about is exploring these possibilities, as seen from a QCA starting point:Pagliarin, S., & Gerrits, L. (2020). Trajectory-based Qualitative Comparative Analysis: Accounting for case-based time dynamics. Methodological Innovations, 13. In this paper the authors introduce the innovative idea of cases as different periods of time in the same location, where each of those subsequent periods of time may have various attributes of interest present or absent, along with an outcome of interest being present or absent. This approach seems to have potential for enabling a systematic approach to within-case investigations complementing what might have been prior cross-case investigations. There is the potential to identify specific attributes, or combinations of these, which are necessary or sufficient for changes to take place within a given case.
Somewhat tangentially...
The same paper reminded me reminded me of some evaluation fieldwork I did in Burkina Faso in 1992, where I was interviewing farmers about the history of their development of a small market garden using irrigation water obtained from a nearby lake. Looking back at the history of the market, which I think was about six years old at the time, I asked them to identify the most significant change that had taken place during the period of time. They identified installation of the water pump in year 198?, and pointed out how it expanded the scale of their cultivation thereafter. I can remember also asking, but with less recall of what they then said, follow-up questions about the most significant change that it taken place in each smaller time period either side of that event, and then its consequences. I was in effect asking them to carve up the history of the garden into segments, and sub-segments, of time not defined by calendar, but by key events – each of which had consequences. These were in effect temporal "cases". Each of these had a configuration of multiple attributes, i.e. being attributes of the nested set of time periods that it belonged to. Associated with each of these were differenting judgements about the the productivity of the market garden. But with our team's time being short supply, I never got the opportunity to gather a full data set, so to speak.
Another of my current interests, prompted by the above conjectures, is the possible use of specific form of Hierarchical Card Sorting (HCS) as a means introducing a temporal element into case-based configurational analysis. The HCS process generates a tree structure of nested binary distinctions between cases. It is concievable that different broad criteria could be introduced for the type of differences being identified at each level of the branching structure. For example, at the top level the "most significant difference" being sought could be specified as being "in terms of funding received", then at the next level, "in terms of outputs generated" , and so on (Criteria 1,2,3 etc in Figure 1 below) .
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| Figure 1 below |
