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Kent Comp Dep May06


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Kent Comp Dep May06

  1. 1. Causality and Probability in the Sciences Federica Russo Philosophy, University of Kent
  2. 2. Overview <ul><li>Top-down vs. bottom-up philosophy </li></ul><ul><li>Causality and Probability: </li></ul><ul><li>evergreen philosophical problems </li></ul><ul><li>Epistemology and methodology </li></ul><ul><li>of causal modelling </li></ul><ul><li>Interpreting probability </li></ul><ul><li>in cancer epidemiology </li></ul>
  3. 3. Top-down vs. bottom-up philosophy <ul><li>Philosophical problems in the sciences: what does it mean? </li></ul><ul><li>Pure vs. applied philosophy </li></ul><ul><li>Practically-oriented philosophy </li></ul>
  4. 4. Evergreen philosophical problems <ul><li>… we are dwarfs on the shoulders of giants … </li></ul><ul><li>The long history of causality </li></ul><ul><li>The shorter but intense history of probability </li></ul>
  5. 5. Epistemology and methodology of causal modelling <ul><li>Causal modelling in the social sciences: </li></ul><ul><li>What’s the rationale ? </li></ul><ul><li>The received view: a rationale of regularity </li></ul><ul><li>My proposal: a rationale of variation </li></ul>
  6. 6. Interpreting probability in cancer epidemiology <ul><li>(joint work with Jon Williamson) </li></ul><ul><li>Cancer epidemiology </li></ul><ul><li>and types of inferences </li></ul><ul><li>The received view … </li></ul><ul><li>to be received yet! </li></ul><ul><li>Our proposal: </li></ul><ul><li>objective Bayesian probabilities </li></ul>
  7. 7. To sum up… <ul><li>Causality and probability are </li></ul><ul><li>fashionable problems still in 2006 </li></ul><ul><li>The bottom-up methodology makes them </li></ul><ul><li>philosophical problems IN the sciences </li></ul><ul><li>Two examples of bottom-up research </li></ul><ul><li>in philosophy: </li></ul><ul><ul><li>variation in causal modelling </li></ul></ul><ul><ul><li>objective Bayesian probabilities </li></ul></ul><ul><ul><li>in cancer epidemiology </li></ul></ul>
  8. 8. What next … <ul><li>Concept of cause in cancer epidemiology, </li></ul><ul><li>full account of levels of causation, </li></ul><ul><li>explanation in causal modelling, … </li></ul><ul><li>And much more … </li></ul>