Thread by @draccoops, In response to @NObermeister ever-useful tweets prompting constructive debates in #sciadvice, here's [...]

In response to @NObermeister ever-useful tweets prompting constructive debates in #sciadvice, here& #39;s my (provocative??) response to this:
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11 reasons why Lawton (2007) is wrong:

1. Scientists are, in part to blame: disciplinarity sections off physical from social science, diminishing the impact of both. Post-normal science and interdisciplinarity address this ( @ArthurCPetersen)

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2. There is actually a disappearingly *small* amount of science, relative to what *could* be there, and what is there, related to 1, is often irrelevant: wrong topic, wrong question, wrong time, wrong place, wrong hypothesis. Co-production and transdisciplinarity help here.

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3. Science is often pretty clear, but then it is also indeterminate: detecting e.g. a high incidence rate tells you nothing about what to do. Translating from causal explanation in policy relies on soc sci (nec but not suff) which is philosophically in contest w/ phys sci

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4. Whether there is public support on option X is a hypothesis that soc sci can help test. Often public supports radical change if done right ( @NickPidgeon1) and lifestyles are for the most not cherished.

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5. This is just normal practice and not a reason science advice fails to impact effectively. Science can play as much a role as any of these, and indeed can be stronger. But key is to make it fit epistemically and ontologically into legal/political space.

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6. Timescales are always mismatched but this hides the fact that scientists are asking the & #39;wrong’ questions. Sci can generate policy issues (climate change) as well as respond to them (COVID), but collecting the right data in right way is central (Cooper 2018)

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7. Ministers (not politicians - there is a difference) are not & #39;caught& #39; btwn sci + industry interest: they *have* to balance them. If & #39;caught’ it is because there is no transdisciplinary skills to integrate diff knowledge as pt 5 above suggests. Sci can help negotiate here.

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8. It& #39;s easy to call out institutional failure: various approaches have been tried in the past to no more success than now. Indicates deeper underlying issues w/ skills & processes & perspectives, including dominant micro-econ approach to policy appraisal. Cost-benefit 2.0?

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9. This isn& #39;t a reason why science has no impact on policy but suggest a failure of sci to be deployed effectively, in part due to the well-understood Euro/US-centrism of most science (aka academic publishing). Respecting & dev local sci capacity essential to progress.

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10. If sci & #39;flies in the face& #39; then it has singularly failed to understand the lived experience of millions who have supported a govt narrative that enabled election. Their expressed reasons may be ‘false& #39; in some sense, but good soc sci can unpack this ( @PDevinewright)

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11. Corruption is not per se a block on science impact - its a block on anyone’s impact. The trick is often to understand timing and framing as well as the logic of policy design. In part, one person& #39;s ‘corruption’ is another person& #39;s ‘redistribution’.

12/13

Key thing *not* mentioned here is the potent but poorly understood #engineeringadvice which is my focus.

Call outs to Nick, Patrick, Arthur ref some key work in this area from energy/env policy, but lots not ref’d...

@UCLSTEaPP

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