Section 2 Manifesto: piecing together fragments of causal information

Gone are the days when we could think of data or information as primarily about numbers. Many of us who are involved in understanding the social world and evaluating interventions within it spend much of our day understanding, presenting and manipulating causal structures and even models of other people’s causal structures.

The fundamental, radical points are these:

• Causal information is primary information. It isn’t something which exists only virtually as a potential conclusion on the basis of observations of non-causal variables. There is a fact of the matter about what causes what, just as there is a fact of the matter about the number of people on a training course.
• Parallel to that, humans’ perception of causation is primary, as primary (and fallible) as our perception, say, of colour. All the things which we know, or think we know, about our world – from the colour of that dress to the way the wind shakes the trees – have already been through a lot of cognitive processing, and none of it is “secondary”. So when we ask stakeholders the “why question” (what causes what in this domain), we are not asking them, first and foremost, about what they deduce from their (non-causal) observations in the way we might as scientists or researchers. That would be a very shaky method; we might be better just to ask them to tell us about their non-causal observations and we could try deducing causality themselves. No, we are asking them about what causes what based on their underlying understanding of the causal structure of their world, which they have pieced together in a number of different ways. That underlying understanding might be somewhat erroneous, but it’s certainly a lot better than ours.

As James Copestake (Copestake, Morsink, and Remnant 2019) says:

“..… attribution claims underpinning the QuIP do not require a control group, nor indeed variation in exposure to the intervention across the sample of respondents interviewed. Rather, causal claims rely on the integrity of ‘within-case’ statements made by respondents themselves”.