I just spent last week at SESYNC which some ecologists might still know better as “the new NCEAS”. It is however different from NCEAS in at least two ways. First the first “S” in SESYNC is “Socio” – not that NCEAS didn’t do plenty of applied ecology with a human dimension, but it is right up front and part of every single project at SESYNC. The second is that the focus is on what SESYNC calls “actionable” science. As some of you know, I have a joint appointment in the Sustainability Solutions Initiative (hereafter SSI) at the University of Maine which has a very similar orientation. Of if you want another hook, the NSF SEES granting program has a very similar orientation. Loyalty demands that I point out that University of Maine’s SSI was the first of these 3 programs!
I should warn you this is a long post. This represents 3+ years of active thinking. Feel free to skim or skip if this is not a topic of interest to you.
I don’t say you need to do the kind of science these three institutions/programs are aiming for. Nor do I say that all science should be of this kind. I still have a healthy component of basic research in my own work and think this needs to keep going. But many, many scientists, especially I find earlier career scientists, want to deliver solutions. And I think I could (if I weren’t lazy) build a case using data from NSF that funding for this kind of science is on the upswing. There is an increasing discomfort with the “loading dock” model of science (do the science, put it on the loading dock, and wait for the adoring users to back up their trucks and do all the work to load it up and use it)
The rest of this post reflect my musings, hard won experience, and education by my colleagues on what it takes to deliver policy-relevant (or actionable science or solutions) .A good part of what I am writing here was learned from my colleagues in SSI*.
So without further justification, let me present my version of the 7 P’s of policy-relevant science (yes I am a sucker for alliterative memory gimmicks). . Also just to be clear I am trained and experienced as an ecologist, so that is obviously my bias, but in this piece I am saying things I believe to apply to science generically (and broadly to include all empirical quantitative researchers and maybe even all academic researchers, certainly not just biophysical science, but remember I can only really claim expertise in ecology).
- Presentation – one common claim is that science would be used for policy decisions more if we only presented it better. This is the idea that scientists are terrible communicators. It is epitomized in Randy Olson’s movie Sizzle. I might even go so far as to say this has been the biggest effort by NSF to make work more useful – they have been conducting extensive media training under the title “Becoming the messenger” conducting workshops all over the country. Personally, I think this one is a big cop out Are there some terribly poor science communicators? Yes. Would all scientists benefit from additional training in communication? Yes. Will the world change if all science were well communicated? NO! There are already plenty of great scientist communicators. There are also plenty of NGO organizations functioning on the boundary with professional communicators repackaging the work of scientists. Improving presentation is relatively cheap and requires little effort and change on the part of scientists – it would be nice if it were the solution. But its not. You can put me down for this being 1% of the problem.
- People – scientists should talk to people who are going to be affected by or care about the problems they addressing. This more commonly goes under the label “stakeholder engagement” and has been a movement building since the social activism of the 1970s and become a US government mandated part of land management under Clinton in the 1990s under the label Community Based Management or CBM. I 100% think policy-relevant science requires engagement with stake-holders (lots of engagement in most cases). However, I don’t think there is much training for scientists in how to do this. And even more importantly, I don’t think there has been much thought in how this process should occur in a way that leaves the scientist doing research instead of just turning into another activist voice at the table. Many social scientists have written research arguing that scientists are just another voice at the table. And of course many politicians are also framing scientists in this just-another-voice box to pursue their own agendas. Thus, while I think stakeholder engagement is critical, I think scientists need to take some real ownership and leadership in figuring out what this looks like and in training our peers. Iin my experience most stakeholders (and most politicians who aren’t pushing an anti-science agenda and many social scientists like Cash) also think science should not just be another voice at the table, but they don’t yet have a well-formed idea of what science-stakeholder engagement should look like either. In my opinion David Cash has written some of the most thoughtful work on this topic (e.g. this piece which coined the idea of “loading dock” research). So to repeat myself, scientists need to be thought leaders in what stakeholder-engaged research looks like. The next 5 P’s are some of my thoughts of what this should look like.
- Problem co-defined – this is probably the most radical but most important of the 7 P’s. The vast majority of scientific questions that get asked come from the scientists themselves. The proportion is a bit lower in natural resource departments but even there a high proportion of the questions are scientist driven. If one steps back though, it is blindingly obvious that if one wants to deliver useful, policy-relevant science, one ought to ask potential stakeholder constituencies and policy makers what science might be useful to them! This is no different than a business finding out what their customers want. This is not to say that scientists are then obligated to do whatever the stakeholders ask. Often they ask impossible questions, questions more expensive than what they or society are willing to pay for, questions outside the expertise of the scientists talking to them, and yes, questions uninteresting to the scientists talking to them. Question definition is best done as a joint negotiation between scientists and stakeholders, and this has been called in the literature as “problem co-definition”. Despite the obviousness of the necessity for this approach, there is an equally obvious reason why it is rarely used – it involves loss of control for the scientists! it is frightening. It is a radical break from existing practice. The experience of SSI with over 20 separate projects is that every time you start a project thinking you know what the stakeholders need but then go ask them before starting, you are usually only somewhere between 0-50% right. Every single SSI project has changed their research questions in fundamental ways in response to stakeholder engagement. This approach fully embraced will radically change the kind of science that is done. That said, in SSI every scientist is still happy with the questions they co-defined and even happier with the fact they are sure the work will be useful. This might be radical, but it might not be as painful as people think at first glance. It might even be good for science for us to be pushed to pursue some questions we avoid because they’re hard!
- Place-based – One common difference between what the researchers want and the stakeholders want is that the stakeholders want much more specific research that is useful to them. In contrast, most scientists are trained to generalize, generalize. It can seem a come down to be asked “what is the population size of deer over the last 5 years in Orono, Maine, USA?” Asking what are the general drivers of deer populations is a more scientific seeming question. And again, natural resource department researchers are already much more used to this kind of research (for which biology/EEB departments sneer at their colleagues for not doing general research and for which the natural research department folks sneer back at their colleagues for building castles in the sky). This is a real issue and research really does fall on a spectrum from highly general to place-based (and organism based and time-specific). To some degree people wanting to do policy-relevant science might just need to sacrifice a bit and move past their comfort zone to do more place-based research. But I would like to argue this dichotomy is made out to be bigger than it really is. How often does a researcher aiming for general results really span more than a handful of sites in a small geographic area at a limited point in time? This is research that is place-based even if it might also be designed to be generalizable. Many scientists can do policy-relevant place-based research funded by policy making agencies (e.g. USDA, state wildlife departments) while still writing very general science papers from the data in addition to the detailed grey-literature place-based reports they deliver.
- Poly-disciplinary – OK – I made this word up to fit my P fetish. Interdisciplinary would be the more common word. Or the hip word would be transdisciplinary (so fully merged the individual disciplines aren’t recognizable). But I think most ecologists recognize that if you want to make the world more sustainability the biggest challenge is humanity. So you better study humanity. The NSF program Coupled-Natural Human (CNH) systems gets at this, although I think it is fair to say that not all policy-relevant science need use a CNH approach (often times the human system completely dominates the natural system and the idea of delicately balanced back-and-forth feedbacks isn’t too useful) nor do all CNH studies lead to policy-relevant science. Instead it is often important to understand the psychology of what motivates people to change, the economics and policy of creating appropriate incentives, human dynamics of population and consumption growth, technology change, etc.
- Post-research-engagement – There is some talk in the literature about co-definition of the problems (see #3 above) and some talk about improving mass-communication (See #1 above), but I think truly successful policy-relevant science requires more – namely stakeholder engagement during research to some degree, but especially after the research is done. As science transitions into policy, there is a very important period of interpreting research. Again scientists like to pretend we don’t do interpretation, but there is no denying it happens in a policy arena. Being actively engaged with stakeholders during this stage is critical. In part it is because stakeholders can help with the communication and help us strip out jargon and avoid obvious pitfalls (like communicating climate change in degrees Celsius instead of Fahrenheit to the American public). More subtle issues of presentation are often important too – for example there have been interesting studies of “boundary objects” – things that sit on the fence between science and policy like maps and what makes them successful or not. But things beyond communication like pulling out what is important to policy, the implications for policy etc also must occur. To my mind this aspect of stake-holder engagement in interpreting research after the research is done (or at least a round of research is done) is the most overlooked and ignored part of doing policy-relevant science. This is why I prefer the phrase co-production of science with its focus on engagement with stakeholders from start-to-end over the more common phrase co-definition of problems or the other common-phrase of stakeholder-engagement that doesn’t given an explicit relationship of stakeholders to research (opening the door to the scientists are just another voice at the table paradigm)
- Personal relationships – stakeholder-engagement has already been discussed above. But it is important to note that successful stake-holder engagement will depend directly on personal relationships built up over time and through informal contacts over meals and what not as well as formal meetings. In a boundary-spanning class I co-taught (more about this below) we brought in 20 people with experience in spanning boundaries between science and policy and literally all 20 people said that in the end personal relationships were the most important thing. This is pretty different from science with its efforts (although never fully successful) to focus on objective progress independent of personal links. But if a legislator is going to take a vote based on science, you can bet they want to know the person who did the science and trust them.
So to do policy relevant science, all you have to do is spend a lot of time with stakeholders, let them have 50% of the job of deciding what research to do, study complex social behaviors in addition biophysical sciences, become more place-based, and open up the research interpretation process to other people and invest time in building relationships with them. No problem, knock it off with a few extra hours of work, right? Of course not! Policy-relevant science involves a fundamental change to the way science is done (again assuming policy relevance is your goal – not all science should have this goal). I have argued above that some aspects like the place-based research and the stakeholder co-defined research need not be as frightening as they seem. But in total, there is no denying doing policy-relevant science is a lot of work! And a big change for many scientists.
So for those scientists who are making this change, or for those educators and administrators trying to facilitate this change, how should the change happen? As always, I am ready with a silly mnemonic. The four T-s of transition.
- Training – This should be obvious to professors, but in truth we have a blind spot – we have gotten so good at teaching ourselves things related to our discipline that we think we can teach ourselves anything. Or that science is the hard part, policy is easy to pick up by osmosis (this is obviously false). If we want scientists to do policy-relevant science we need to train them in skills related to the 7 P’s and this includes soft skills like facilitation To my mind this can be best summarized as the task of boundary-spanning. A transformative event for me (and I think the 3 colleagues I co-taught the course with – David Hart, Laura Lindenfeld and Kathleen Bell) was teaching a 1 week intensive course in boundary spanning for graduate students. In addition to reading some of the literature and theory of boundary spanning (probably a whole other post in there), we brought in panels of people who successfully span boundaries and had them speak about what they saw as key success factors. But whatever you call it, there are a lot of skills that boundary-spanning scientists doing policy-relevant science need. Media training (P #1) is just the tip of the iceberg.
- Teams – the biggest error in thinking is that one person can or should do all 7 P’s. It is a rather laughable idea actually when you really stop to think about it. This means that policy-relevant science almost always happens in teams. In these teams everybody needs to have the rudiments of the 7P’s but different individuals with different strengths and expertise can complement each other to actually fulfill the full range of the 7 P’s.
- Tag teams- policy relevant science can also happen by one person doing one piece and making it available in a public manner and then somebody else picking it up and doing another piece, not unlike children’s tag-teams where when you tag somebody you go out and they step in to do something (or WWF wrestling if you prefer). People can do this without ever thinking of themselves as a team or ever even meeting. There is obviously a continuum from strong teams through weak coalitions to tag-team processes. And tag-teams are dangerously close to the loading dock model that was derided above and in the piece linked to above by Cash. Thus I expect the majority of successful policy-making will occur closer to the team than the tag end of the spectrum. But some good policy-relevant science happens through tag if people do it in a thoughtful way. And no doubt this approach can be used to channel more basic research in useful ways. As an extreme example you don’t need stakeholder engagement to know that cold-fusion or understanding the causes of extinction are important research topics. Just don’t use this as a cop-out to avoid teams.
- Thinking – I’m talking about big changes. Scientists need to apply their academic approach of discussion, analysis and data to the 7 P’s and success factors in doing policy-relevant science. Social scientists have been the ones studying and writing about this problem most to date. Many of them are doing a good job. A few of them in my opinion don’t get biophysical research at all. But it is kind of ironic that if the ideas which emerge are things like teams and inter-disciplinarity that the topic of how to policy-relevant science is not team-based and inter-disciplinarity. A full understanding of how best to do policy-relevant science needs to include the biophysical scientist’s expertise and perspectives too. This has not been happening enough.
You can call everything I have talked about boundary spanning or co-production of science (as Cash that I cited above does). I think both of these phrases are useful. But whatever you call it, it is a lot of work and the world needs more of it. And as a scientist trying to learn this material, I found very little published material (journal articles or otherwise to help me learn. That needs to change.
I am very curious to hear what others think. Again I don’t want this to turn into a debate about whether policy-relevant science should happen and scientists should be part of it. They should but not everybody should be forced to do so – basic science is important to. For those who would describe themselves as already engaged in policy relevant science, what did I get right or wrong? For those just starting out, was this helpful? what are your impressions? For those who have never done policy relevant science, does this scare you away or appeal to you?
* Including amongst many others David Hart, Tim Waring, Kathleen Bell, Mac Hunter, Aram Calhoun, Laura Lindenfeld and Shaleen Jain
A nicely framed way of thinking about policy-relevant science, Brian. I’ve been living in D.C. for the past year, and so have been thinking such things myself. Unfortunately, my impression is that we’re actually further behind the curve than you make out. I went on BESC’s (Biological and Ecological Sciences Coalition) Policy Day of lobbying for science funding (especially NSF funding). Before heading to Capitol Hill, we heard from a number of professionals pursuing science policy in the city. The story of one stuck with me: one of his proudest accomplishments was just bringing science to the table; he had spent several years getting a then-lowly office of science within the Department of the Interior to report directly to the director, rather than having several layers of management between science recommendators and implementors. This is important, because the science case often gets changed, watered-down, or incomprehensible when it is relayed.
This was made clear to me several weeks earlier when I sat in on part of the Bowman v. Monsanto Supreme Court case that was recently decided. I only had the chance to hear a few minutes, but what I heard was depressing. The lawyer for Monsanto was trying to explain to the justices some of the science behind how a roundup-ready seed is created. The lawyer did reasonably good job simplifying the concepts so the justices could grasp them; but it was clear the justices didn’t really understand the science — Scalia was outright flippant, asking if you could use a gene gun to rob a bank. But even the more liberal judges were somewhat perplexed and dismissive of the new-fangled technology. Worse, when they asked questions about the science, the lawyer couldn’t answer them. Understanding the science behind genetic modification is really important in figuring out how patenting genes is different from patenting machines; the fact that the country’s top judges don’t understand the science (and in some cases have no interest in understanding the science) is a real problem.
So I’m not sure that science is even AT the table much of the time. It seems to me that before science becomes actionable, there has to be a policy-maker receptive to even considering a science perspective. And there’s got to be a higher general comprehension of why science even has value. And that’s all lunches, golf-games, and handshakes; not necessarily the sort of things most scientists want to get deeply into. In fact, at the Policy Day, going into science policy was often framed as a sacrifice: if you “take one for the team” (and go into science policy instead of doing actual science), you can make a (small) difference. Many of the young people at Policy Day appeared interested in policy (in part) because the job market in science is so bleak.
I hope SESYNC, SSI, SEES, and their ilk have some real impact, but I’m not holding my breath.
Thanks for sharing your experiences. They ring true to me from my experiences here in Maine. Very often science isn’t at the table. And even as a scientist I don’t think it ever should be the only thing at the table (lives, costs, etc should be in the discussion too). Some days I think we live in a uniquely cynical age for disrespecting science, other times, I think it is part of the postmodern trajectory where nobody has authority and other days, I think it is just an ongoing skirmish that hasn’t changed much (took 50 years to have smoking recognized as harmful). What to do about that as a society is a huge topic that I certainly don’t have the answer to.
What to do as an individual is another question to which I at least have answers, albeit many valid answers. They include never going into science and becoming a lawyer, politician or activist. They include training in science and transitioning into policy (more or less what you describe). Just giving up and ignoring it and doing science that is fun and interesting irrespective of policy relevance is an option. Right now and for this year and probably this decade, I am doing a fourth option, remaining a research scientist but trying to reach across the divide a bit and be mindful of what kind of science I do and how I do it.
I do think that how hopeless things are varies from question to question and with scale. For example here in Maine many town planners (the level at which many decisions are made) are very amenable to expert help (and a good number aren’t too). And good research on how to improve conservation very often gets translated into policy by conservation staff at agencies (and again sometimes not). Sometimes I think the giant overarching questions are too intimidating to contemplate. I don’t think I could stand to be doing science policy in DC on really big questions. But things often look much more tractable on smaller questions and scales.
I was also at the BESC Congressional Visit Day (hi Margaret!) and I believe it was Alan Thornhill who said that science has an influence on the decisions being made if science a seat at the table. As a young person who was at that table (it was literally a round table discussion), I want to make it clear that I was not there just because the tenure-track job market is weak. My interest in policy-relevant science stems from this need, as Brian recognized, to deliver solutions. I don’t know if this is an early-career thing (abundant enthusiasm & bright-eyed naiveté) or a generational thing (growing up in an age where we learned about the science climate change, but then graduating into a world where policy seemed to be completely ignoring the science). I was lucky enough to spend two years at UVM’s Field Naturalist program before beginning my (more traditional ecology) PhD, and I think interdisciplinary programs like Vermont’s do an incredible job of introducing some of the training and “7 P” concepts to young scientists, so that they (we) enter the job market (or the next phase of grad school) already aware of the challenges (and rewards) of doing policy-relevant science. This seems to be a more efficient route than teaching old dogs new tricks…
Hi Caitlin – great to hear another perspective.
I do think this urge to do solutions/policy-oriented science is career stage related, but not for why you might think. I see it mostly in early career but also late career (think of Paul Ehrlich, Hal Mooney, Peter Raven, Steve Carpenter). I think it is a function of once you step on that academic treadmill it is just really hard to break out of the expectations that are focused on papers that get in top journals (meaning very general). And as I noted, solutions-oriented work is dang time consuming and often not highly general. The two are not easily compatible with academic expectations.
I want to be clear that I am not saying you cannot do solutions oriented science mid-career at a research university. At Maine there are many people doing so and so far, knock on wood, all are getting tenure and being rated as successes. But Maine is pretty strongly permeated by its land-grant mission and is not a tip-top tier RI school. I often wonder what would have happened if I’d made this switch at say Arizona or McGill. So it is possible I think in many places but the expectations vs reality match might just be too great for some places. And it requires a bit of being willing to be a risk taker, thought leader, trend-bucker mentality.
And as Jeremy noted, the times are changing. I think more and more institutions will begin to look on this kind of work favorably. A postdoc I mentored in SSI got his tenure-track job BECAUSE of his 7Ps solutions-oriented skills. It was a traditional type job in a traditional department. He had to have the publications and credibility within his field. But having that, it was the difference maker that set him above the two other candidates that made the short list and who were roughly equal in the traditional metrics.
I didn’t know about UVMs program so thanks for mentioning that.
Hi Caitlin! I didn’t mean to imply that everyone there was there because of a tough job market; that’s why I wrote “(in part)”. But I did talk with several people who had assumed initially they’d be pursuing primarily a research career and started to look around for other alternatives when they realized how hard it was to get a job. I do think that the majority of people at the BESC Policy Day were truly interested in pursuing science policy — how they got there obviously varied from person to person.
Great post Brian, and well-timed. BioDiverse Perspectives has an interview up with Peter Kareiva that echoes many of your comments, particularly the need for researchers who want to do policy-relevant researchers to let others define what questions they ask:
Well-timed as well in the sense that government research budgets are shrinking in real terms, and increasingly directed towards applied work. You note, and I agree 100%, that fundamental research is still worth doing. But for various reasons, arguments for fundamental research have increasingly little traction with governments. In future, I think scientists increasingly are going to have to do applied research whether they like it or not. Because attempts to pretend that fundamental work is really applied are increasingly going to be seen through or ignored. (As with much biodiversity-ecosystem function research, a point noted by Peter Kareiva in that interview.)
I enjoyed the Kareiva interview as well. I think he is seen as a bit of a traitor by some ecologists. But, while I don’t agree with everything he says, I do see him as a realist working hard to bridge the gap which is more than most people can say. My favorite Kareiva quote is “in human society, corporations are keystone species”. Sticking your fingers in your ears and denying reality isn’t going to do much for this planet.
For better or worse (which has been debated on this blog in the past and of course there are valid points of view on both sides) I think it is empirically true that the funding trends are away from basic research and towards applied globally. When you visit a place like China or even Australia, you realize it never was primarily oriented towards basic research in some places.
And further to Margaret’s comments about science often not having a seat at the table, that’s not the worst-case scenario. The worst case scenario is that science doesn’t even exist to have a seat at the table. The complete defunding of entire fields (starting with political science) is now a possibility being seriously considered in Congress:
And in case anyone was under any illusions that this is about substantive issues on which one could bring logical argument and data to bear, as opposed to the most obvious sort of political calculation:
Here’s a journal article about bridging the science-policy divide, co-authored by policy people and scientists:
Gibbons et al. (2008) Some practical suggestions for improving engagement between researchers and policy-makers in natural resource management. Ecological Management & Restoration 9(3): 182-186.
The journal site:
Click to access ecomanagement.pdf
Looks like a good article. Thanks for the link
Thanks for this great post Brian. One thing not mentioned that I think is often overlooked but important is the distinction between policy and science. It may seem obvious, but I have found that it is not always clear where science stops and policy begins. Perhaps this falls under either “Presentation” or “Problem co-defined” in your 7 Ps, but I think for science-policy collaborations to work most effectively, everyone “at the table” needs to be clear on which issues science can address and which they can’t. I’ve seen many discussions related to threatened and endangered species management get bogged down because this distinction was neither articulated nor, I think, clear in people’s minds.
Great point. I think scientists acting like they’re the only ones to be listened to or having a valid perspective is a major barrier (and I’m too lazy to dig up the citations but I know there is a lot of literature showing that the perceived arrogance of scientists is a major reason stakeholders hesitate to engage with scientists). As you note there are a lot of important topics and questions that go into policy that science either cannot currently or never will be able to weigh in.
I am very firmly in the school that for scientists in public settings, “honesty is the best policy”. And that most definitely includes acknowledge fundamental limits.
Our need to put error bars and qualifications on everything is a much more specific topic that doesn’t have simple answers (and could be a whole post in itself).
But on the broader issues that many topics are beyond our current scientific knowledge I agree that clarity around this is important for both the scientists and stakeholders
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At the risk of utter embarrassment of my eldest, here are his “old man’s” comments on reading his blog and your responses. The following may be a bit off topic, but nonetheless important, I would argue, in the “operation” of science in universities (indeed, broader, too).
To establish my (non)credentials to enter such a conversation, i was an early STEM type, supported throughout my PhD by the NDEA (remember? the post-Sputnik support of budding science and math types) in applied math, namely operations research. I am afraid I almost immediately “fell” to becoming a university administrator. One of the most rewarding aspects of doing so, though, has been continued contact with faculty and discussing their achievements.
And so, my point. I shared breakfast this morning with the chair of Mechanical and Materials Engineering at Hopkins, a fellow Stanford grad from a small town in Ohio and a nano-materials and wave mechanics guy. He is quite accomplished, including a seat on a prestigious DARPA board that pushes the government limits in topic exploration, and builds linkages between academic scientists and industry. We were discussing a post (titled something like vice dean of research) in the engineering school that he is helping recruit to. The question posited is whether a “never-academic” person who is otherwise a very bright, connected, young scientist can serve that role. They are looking for a “connector” who can encourage collaboration across the academic units at Hopkins, including the biosciences, public health, etc. AND links to government and industry AND helping young faculty become familiar with how best to prosper within their environment. To the credit of the leadership of the school, most of the department chairs are of the opinion of “bring him on.”
We concluded (before I read this blog) that something like (at least most of) Brian’s 7 Ps were the right characteristics, coupled with some other skills, for success in a research administration position, even though never a faculty member.
Somewhat related, too, is a recent conversation with a Baltimore family physician who is building into her “curriculum” for her residents material on the obligation for them to connect with the community of their practice (not just their patients) and serve broader social needs.
You colleagues of Brian should know that I instilled these Ps in him while still on my lap. 🙂
A pleasant surprise to hear from you here! Thanks for generalizing the conversation outside ecology. Although I don’t have much personal experience, I do think the same principles apply.
The big question in your engineering college scenario is whether the department chairs will be supportive of faculty spending more time “on the boundary” or “being relevant” at the cost of traditional scorekeeping like publications and grants. There is no free lunch here – tradeoffs do occur. I think a lot of people (including NSF) are pretending like if you just work smarter there is no trade-off, but I don’t believe it. It would be a real change of culture to do it at a top 20 research institution like Johns Hopkins.
I love this! My father was my field assistant for two years, but I would keel over from shock if he commented on one of my posts! 🙂
Well, just a geologist here. But I’ll share some thoughts.
I think it’s important for scientists in policy-related research to take a much harder look at the robustness of their work – understand and question the myriad assumptions and simplifications that almost always underlie the ideas they’re working with. Assess the quality of your data realistically. When you affect people’s lives and livelihoods, work that’s consistent with curent thinking isn’t good enough: it’s your responsibility to ensure that your work is accurate.
It’s funny that you mention Paul Erlich who, I suspect, is more famous for his failure than his success. I think we should all be relived that we didn’t follow his recommendations.
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Hi, Brian, this is indeed a great and thoughtful post.
From our Australian experience, though, I’m curious that you don’t have (yet!) another P – Participation. Co-design of research is one thing, but co-production of knowledge is another equally powerful step. As with your other points, it’s not for all cases or all people, and it also is challenging, but having decision-makers involved in the process of doing the research can be by far the most effective means of ‘communication’ there is. This can occur at various levels from sitting on a closely engaged advisory group, though to really being part of the research team, but results in immediate ownership of the results (and, incidentally, joint ownership of the genuine challenges and potential for failure in some complex research – this has protected us from contractual angst in more than one late milestone!). Of course there is still the question of how the results from such research get passed on to others who weren’t actually involved in the research, but your current schema has that concern anyway. Perhaps you mean this as part of your Ps 4-7 but it doesn’t come through strongly if so.
I also like your emphasis that not everyone should be doing all this (but, by the way, everyone should respect the need for some people to do it, which isn’t always the case). That raises a key question that we don;t normally articulate – when should these more time and resource intensive efforts be put in (on the basis that results will be very sub-optimal otherwise) and when are simpler more ‘traditional’ approaches adequate to give good results?
Ta, Mark SS.
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