Saturday, December 26, 2015

Meta versus macro theories of change

A macro-ToC is single ToC that seek to aggregate into one view the contents of many micro-ToCs. For example, the aggregation of many project-specific ToCs  into an single country-level ToC. There are two risks with this approach:

  1. The loss of detail involved in this aggregation will lead to a loss of measurability, which presents problems for evaluability of a macro-ToC
  2. Even where the macro-ToC can be tested the relevance of the results to a specific project could be contested, because individual projects could challenge the macro-ToC as not being an adequate representation of their project intentions. 
The alternative to a macro-ToC is something that could be called a meta-ToC. A meta-theory is a theory about theories. A meta-ToC would be a structured set of ideas about the significant differences between various ToCs.  These differences might be of various kinds e.g. about the context, the intervention, the intended beneficiaries, or any mediating causal mechanisms. Consider the following (imagined) structure. This is in effect a nested classification of projects. Each branch represents what might be seen by a respondent as significant differences between projects, ideally as apparent in the contents of their ToCs and associated documents. This kind of structure can be developed by participatory or expert judgement methods  (See PS 2 link below for how). The former is preferable because it could increase buy in to the final representation by the constituent projects and their associated ToCs.
The virtue of this approach is that if well done, each difference in the tree structure represents the seed of a hypothesis that could be the focus of attention in a macro evaluation. That is, the "IF.." part of an "IF..THEN.." statement. If each difference represents the most significant difference, the respondents could then be asked a follow-up question: "What difference has or will this difference made?" Combined with the original difference, the answers to this second questions generates what are are essentially hypotheses (IF...THEN...statements), ones that should be testable by comparing the projects fitting into the two categories described.

Some of these differences will be more worthwhile testing than others, if they cover more projects. For example, in the tree structure above, the difference in "Number of funders" applies to all five projects, whereas the difference in "Geographic scale of project" only applies to two projects. More important differences, that apply to more projects, will also by definition, have more cases that can be compared to each other

It is also possible to identify compound hypotheses worth testing. That is, "IF...AND...THEN..." type statements. Participants could be asked to walk down each branch in turn and indicate at each branch point "Which of these types of projects do you think has/will be the most successful?" The combination of project attributes described by a given branch is the configuration of conditions hypothesised to lead to the result predicted. Knowledge about which of these are more effective could be practically useful. 

In summary: This meta-theory approaches maximises the use of diversity that can be present in a large portfolio of activities, rather than aggregating it out of existence. Or more accurately, out of visibility.

PS 1: These thoughts have been prompted by my experience of being involved in a number of macro-evaluations of projects in recent years.

PS 2: For more on creating such nested classifications see

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