A postdoc asked a question about being prescriptive and/or normative in academic papers, noting that some of the people with the most successful scientific careers were scientist/activists who did not shy away from saying in their technical work what we should do or what is good and what is bad.

My response:

It is fine to say “I think we should do XYZ” or “XYZ is good [or bad]” in an opinion piece in academic or informal settings.

But is it OK to make those kinds of statements in regular academic research papers?

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A starting point is that there are multiple paths and strategies to success and you have to do something that fits your personal style and also takes account the reality of the job market.

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I was trained on Hume’s distinction between empirical and prescriptive/normative statements.

My feeling has always been that we as scientists are trained to generate and disseminate information and our opining on public issues was just our hobby, not our profession.

That said, I am not above language of the sort: “Policy makers should consider doing XYZ” rather than coming right out and saying “Do XYZ”. 

This may seem rhetorical artifice, but there is implicit acknowledgement in that construct that I may be wrong in my recommendation when a broader range of facts is considered.

I am probably near one end of the spectrum of wanting to keep recommendations to a minimum in academic papers (research suggestions, factors for policy consideration).

Others say that the distinction between opinion/informal pieces and scientific/technical reports is artificial and all that is required is transparency.

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When something is written in an academic paper, it should be true and you should stand behind it for all time.

Usually the errors are not in what you did, but errors in interpreting the implications of what you did. Often the error is believing your result applies more generally than it does.

When I look back since graduate school, my policy prescriptions have evolved, but I stand by all of the basic findings I have published over the years.

ON ATTRIBUTING DAMAGE TO CLIMATE CHANGE

To attribute damage to climate change, in principle we would like to fully understand the state of the system with climate change and then subtract out a counterfactual without climate change.

If we wanted to estimate the impact of current climate change on flood damage we could seek to understand current flood damage and then subtract off our best estimate of what would have happened in the absence of climate change.

Obviously, the stochastic nature of weather makes attribution challenging, but here I am after another conceptual issue.

We could have said, “The flood damage would not have been so bad had we not built valuable infrastructure in harm’s way.”

How could we attribute damage to building in harm’s way?

We could adopt a procedure that is similar to climate attribution: We could ascertain the observed damage under current conditions and subtract off what the damages would have been had we not built in harm’s way.

If we assume that damage would occur if and only if there were both climate change and a history of building in harm’s way, then this procedure would attribute the full cost of the damage to each of climate change and building in harm’s way.

The damage would not have occurred had we not changed climate and the damage would not have occurred had we not built in harm’s way.

Is there a truth to the matter in this case what fraction of the flood damage should be attributed to climate change and what fraction to building in harm’s way?

“Responsibility” is a social construct. Bad outcomes are often the consequence of a confluence of a series of unfortunate events, and there is no unique way of partitioning responsibility across the range of events that are jointly sufficient to produce the bad outcome.

We can agree on the empirical facts but disagree on how much responsibility for damage should (or should not) be attributed to climate change.

ADDENDUM

As a practical matter, as a climate modeler, if I wanted to estimate climate damage I would subtract results from a simulation without climate change from results of a simulation with climate damage, and I would attribute that full difference to climate change.

Also as a practical matter, if I were a coastal hazards investigator and I wanted to estimate the damage caused by inappropriate coastal development, I might compare cases with the same weather but with and without coastal development, and attribute the full difference to coastal development.

If a large number of studies examined damage with and without various factors (e.g., damage from failure to build adequate flood control systems), the sum of all of the attributed amounts could greatly exceed total damage.

There is value in these “all other things equal” studies, but in the real world other things are seldom equal.