In my field of research (a sociologist in public health), I'm constantly being asked to account for and explain my 'leaps of faith', which I think is fair enough to ask. This is most obvious in my research on the sociology of trust, where researchers, often implicitly and unknowingly, assume Simmel's position of trust being a leap of faith (which still held sway with Giddens and Luhmann too). Whilst such a 'leap' (i.e. to invest trust) may occur in the absence of conscious/rationalistic thought, one can still use retroductive reasoning (from critical realism) as a way of transparently 'laying bare' how you made the decision. Similarly, retroductive reasoning or logic seems to be a formal process for what you're talking about in terms of interpolating from the evidence in a RR. All scientists (natural, social, biomedical, physical etc) use all forms of inductive, deductive, abductive and retroductive logic in their research (often implicitly), so maybe we need to be clear (and have a 'name' for our reasoning)?
Whilst this all sounds great, retroduction still isn't always viewed as 'scientific' within sociology - I submitted a paper to a very good sociology journal recently using retroductive logic to make a distinction between trust and dependence (patients in our study said they trusted their doctors but also said they had 'no choice' etc, which for us does not constitute trust, but a form of dependence) - one of the reviewers loved it but the other just couldn't get his/her head around the 'logical process' we had used to make this 'semantic leap' - this may in part be my lack of clarity in laying bare the retroductive process, but may also be continual problems between the supposed value free nature of 'proper' science (it apparently involves facts, not reasoning or argument - I wish some of my biomedical colleagues would read Kuhn) and the 'value laden' notion of reasoning.
Sorry if this seems like a rant...... it was meant to be constructive but ended up like therapy:)
Professor Paul Ward
Discipline of Public Health
On 10/08/2011, at 3:13 AM, "Geoff Wong" <[log in to unmask]> wrote:
> This thread could be boiled down to two important questions:
> 1) In a realist synthesis (RS) should reviewers infer/make assumptions/interpret beyond what is reported in the included studies?
> 2) If we do make these 'leaps' how do we know these are 'true'?
> GOING 'BEYOND' THE REPORTED DATA
> There was agreement that this was in fact almost a requirement of RS. One argument was that there would rarely ever be enough data to banish all uncetainties and so staying too close to the data would result in a RS ending with the cliched phrase of 'more research is needed'.
> One strength of RS was that it is specifically geared at requiring this leap to be made - for example in working out what a mechansims might be that is generating the outcome of interest. Such leaps were seen as being the value that RS adds.
> Reviewers were in a good position to make such leaps as they would be immersed in the literature on the topic and had the advantages of being able to look beyond just the topic and/or across studies and "critical distance". The key was to be explicit and explain that inferences/assumptions/extrapolations/interpretations were being made.
> THE 'TRUTH'
> If you are a realist you would not expect to ever get to the 'truth' but you might expect to get closer and closer :-)
> There are many challenges associated with making inferences/assumptions/extrapolations/interpretations.
> How do you or others know if you haven't just "hijacked" the data for your own ends?
> How do you know is your 'leap' is 'true'?
> These questions raise issues about 'quality' and 'rigour' and so on. As a secondary researcher (unlike in primary research such as realist evaluation), you can't go back and ask participants what they think about your leaps. However, you can be TRANSPARENT about what you did and why. This should allow others to see for themselves that your 'leap' was COHERENT and PLAUSIBLE. As one contributer put it "... this is what I think is going on, and this is the way I came to that decision...". Briefly, any judgement of coherence and plausibility would rest on how well your explanation fits in with not only what we already know, but also with the reported data in included studies.
> Transparency might involve reporting revelant detail and also processes - such as searching was designed to get the 'right' kind of data, that the review team was reflextive etc.
> Others can then judge for themselves the coherence and plausibility of your inferences/assumptions/extrapolations/interpretations. If they don't like it, then it's up to them to provide an alternative coherent and plausible inferences/assumptions/extrapolations/interpretations.
> This thread came up with two pther points which I hav just noted here but not explored further.
> - Is there such a thing as "interpretation free" research?
> - Any outputs for a review should think about who the audience might be and tailor their output to their needs - and if possible make them think!
> A final point arose which was about how do you come up with theories... this will be covered in another Interim summary.