Prof John Worrall LAK 3.02

This course is available on the BSc in Philosophy and Economics, BSc in Philosophy, Logic and Scientific Method and BSc in Politics and Philosophy. This course is available as an outside option to students on other programmes where regulations permit and to General Course students.

Although the emphasis throughout will be on ideas rather than formal techniques and although all the ideas will be explained simply and intuitively, much of the evidence relevant for policy is evidence about probabilities and so the course will centrally involve issues about the correct interpretation of  probability and statistics. Although no detailed formal manipulations will be required, students will need to feel happy thinking about the intuitive ideas underlying probability and statistics.

Although the emphasis throughout will be on ideas rather than formal techniques and although all the ideas will be explained simply and intuitively, much of the evidence relevant for policy is evidence about probabilities and so the course will centrally involve issues about the correct interpretation of  probability and statistics. Although no detailed formal manipulations will be required, students will need to feel happy thinking about the intuitive ideas underlying probability and statistics.

Good policy decisions - whether concerning climate, conservation, international development, poverty, education, medicine, health, or whatever - require a rationally-based view of whether the proposed policy will (or is likely to) bring about the intended outcome: will reducing CO2 emissions reduce global warming? will mass mammography decrease deaths from breast cancer? will reducing class sizes enhance scholastic achievement?  The obvious suggestion is that such views are rationally-based just in case they are based on evidence.  Reducing class sizes, for example, is a good policy for enhancing scholastic achievement just in case there is evidence that the policy works. But what counts as evidence? What happens when different kinds of evidence pull in opposite directions? Are certain types of evidence more telling than others? And if so, why?  Does evidence that the policy works in one country mean that we should have confidence that it will work in another country?  These are the central issues addressed in this course.  It might seem initially that only experts, only scientists involved in the field, can tell what counts as good evidence. But this is not true. You can learn how to be ‘evidence-savvy’, how to ask the right questions about evidence, without needing to know the detailed science involved.

Very few, if any, policies are guaranteed always to work in every member of the population to which they are applied. Nearly always the issue is whether the policy will increase the probability of the desired outcome: is it probable that mass mammography will reduce breast cancer deaths? is it probable that reducing CO2 emissions to extent x will decrease global warming to extent y? will making drug D for condition C available on the NHS have a positive effect on the average (i.e. not for every patient suffering from C but probabilistically)? So an important part of the course will be involved with probabilities, statistics, risk-assessment and the like.

10 hours of lectures and 10 hours of classes in the LT.

Students will be expected to produce 1 essay in the LT.

Gigerenzer, G. (2002) Reckoning with Risk: Learning to Live with Uncertainty;  Cartwright, N. and Hardie, J. (2012) Evidence-Based Policy: A Practical Guide to Doing it Better; Worrall, J 'Evidence in Medicine and Evidence-Based Medicine', Philosophy Compass 2007.

This will be supplied at the beginning of the course via an electronic pack organised through the Library

Exam (67%, duration: 2 hours) in the main exam period.
Essay (33%, 2000 words) in April.

The summative essay can be a more developed version of the second formative essay in the light of feedback.