What Policymakers Need to Know about Scientists
In my previous post, I excerpted 20 points from an article in The Guardian that tried to give scientists advice on what they needed to know about policy-making in order to be more effective in working with policymakers. That article was actually inspired by an earlier article in The Guardian that tried to explain scientists to policymakers. So, although I know most of this audience consists of scientists and engineers, I thought you might find it interesting to see how others explain our work. Once again, I present only the bullet points (complete with the original spelling) and urge the reader to go to the original article for further explanations.
With that, here are the recommended 20 things policymakers should know about scientists:
1. Differences and chance cause variation
2. No measurement is exact
3. Bias is rife
4. Bigger is usually better for sample size
5. Correlation does not imply causation
6. Regression to the mean can mislead
7. Extrapolating beyond the data is risky
8. Beware the base-rate fallacy
9. Controls are important
10. Randomisation avoids bias
11. Seek replication, not pseudoreplication
12. Scientists are human
13. Significance is significant
14. Separate no effect from non-significance
15. Effect size matters
16. Data can be dredged or cherry picked
17. Extreme measurements may mislead
18. Study relevance limits generalisations
19. Feelings influence risk perception
20. Dependencies change the risks
Once again, the comments provide some different perspectives, and perhaps my own list would be a little different. But overall, I think most of the points are valid, and they should provide food for thought for all of us.***
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