San sebastian mechanisms

2,209 views
2,209 views

Published on

Introduction to mechanisms

Published in: Technology, Spiritual
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
2,209
On SlideShare
0
From Embeds
0
Number of Embeds
1,014
Actions
Shares
0
Downloads
1
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide
  • Field guide, gentle introductionSystematise my knowledge of the field
  • Many topicsMade a selection: subjective – what I find most interesting / important in the debateHappy to skip some or linger more on others depending on your interest
  • What kind of phenomena to account for causallyWhat kind of phenomena to exclude (causally)Mention ontic explanation – it will come back
  • Recall the context: when I started, Salmon was still the dominant paradigm
  • What concept of function – role-functions, isolated descriptionsMechanistic explanation in all its variants – see e.g. Craver on inter-level or on mutual manipulabilityDecomposition/re-composition – discovery and confirmation
  • Organisation: an epistemic aspect: the description of the functioning does the explainingRecursive decomposition can be interpreted as a mechanismBackwards: aetiological senseDownwards: go down into the mechanismsBut also go up to the mechanism!
  • Conceptual pluralism:Causation one thing, many wordsDepending on scientific area?Monism: one thing one conceptAccounts of dependence vs accounts of production
  • Interestingly, CIAO! Seeks to develop diagnosis along the lines of RWT.Comparisons between social systems and designed systems (enterprises) – functional architecture, functional individuation much easier
  • San sebastian mechanisms

    1. 1. Mechanisms in the Sciences: A Field Guide Federica Russo Center Leo Apostel, VUB Centre for Reasoning, Kent
    2. 2. Overview1. The received view 6. Evidence of mechanisms2. The consensus 7. Mechanisms and3. Why mechanisms? reasoning4. Mechanisms on the stage 8. Pluralism and monism5. What are mechanisms for? 9. Practical (scientific) use 2
    3. 3. 1THE RECEIVED VIEW 3
    4. 4. Machamer, Darden and Craver:‘Mechanisms are entities and activities organized such that they are productive of regular changes from start or set-up to finish or termination conditions.’ (Machamer, Darden and Craver 2000 p3.)Glennan: ‘A mechanism for a behavior is a complex system that produces that behavior by the interaction of a number of parts, where the interactions between parts can be characterized by direct, invariant, change-relating generalizations.’ (Glennan 2002b pS344.)Bechtel and Abrahamsen:‘A mechanism is a structure performing a function in virtue of its component parts, component operations, and their organization. The orchestrated functioning of the mechanism is responsible for one or more phenomena.’ (Bechtel and Abrahamsen 2005 p423.) 4
    5. 5. 2THE CONSENSUS 5
    6. 6. Illari& Williamson: A mechanism for a phenomenon is composed of entities and activitiesorganized so that they are responsible for the phenomenon.’ (2012, p.120)Illari& Williamson give up on: Regularity Start up, finishing conditions Complex systemMechanistic explanation: Identification of the phenomenon Identification of entities and activities involved Identification of the organisation 6
    7. 7. 3WHY MECHANISMS? 7
    8. 8. Once upon a time: process theoriesCausation in physicsSalmon-Dowe approach A development of Russell-Reichenbach (world-lines, at-at theory)Salmon: ‘put the cause into because’ The because is given by the physical, causal process (Ontic explanation) 8
    9. 9. Processes in biology?MDC (2000, p. 7): Although we acknowledge the possibility that Salmon’s analysis may be all there is to certain fundamental types of interactions in physics, his analysis is silent as to the character of the productivity in the activities investigated by many other sciences. Mere talk of transmission of a mark or exchange of a conserved quantity does not exhaust what these scientists know about productive activities and about how activities effect regular changes in mechanisms. 9
    10. 10. Processes in social science?Russo (2009, p.26):The need to look directly at social scientists’ work was motivated by a possible difference between causal claims that involve reasonably clear causal mechanisms and causal claims that do not. I went through five case studies, and it turned out that none of them contains concepts typical of aleatory causality in order to get an understanding of causal relations—to borrow Salmon’s terminology again. Instead, statistical causality is definitively preferred. However, to prefer statistical causality does not ipso facto rule out mechanisms from the causal talk. […] the question is not whether or not we aim at identifying causal mechanisms, rather, how do we come to identify them. Causal mechanisms are not identified through causal processes and interactions, but, according to the social scientists’ practice, they are statistically modelled. 10
    11. 11. 4MECHANISMS ON THE STAGE 11
    12. 12. Biology and neuroscienceBechtel, Craver, Darden, MDC, … Functional individuation Mechanistic explanation Decomposition / re-composition … 12
    13. 13. Social scienceAnalytical sociologists, Little, Russo (&Mouchart, Wunsch), … Mechanisms and Methodological individualism Statistical modelling Social regularities Human action Social ontology … 13
    14. 14. 5WHAT ARE MECHANISMS FOR? 14
    15. 15. ExplanationOntic and epistemic mechanistic explanations Craver, Bechtel (biology / neuroscience) Illari: ‘reconciliation’ of the ontic and epistemic Russo et al (social science)Explain … how? Organisation, recursive decomposition Backwards, downwards, or upwards 15
    16. 16. Self-rated health in the Baltic countries 1994-1999 16
    17. 17. What are the causes of self-rated health in the Baltic countries in the ‘90s? X Y Take the joint probability distribution + Make assumptions P(Education, Locus of Control, Physical Health, …, Self-Rated Health) P(X1, X1, X3, …Y) perform a recursive decomposition of the type P(Y)= P(X1) P(X3) P(X2|X3) … P(Y|X2, X3) Read as: Self-Rated Health depends on Education; on Locus of Control through Psychological distress; on Alcohol Consumption which also depends on Physical Health; … 17
    18. 18. Speaking of ‘upwards’Darden: Often biologists engage in much investigative work to discover the level at which a given mechanism operates. Geneticists worked to find the operative level for genetic linkage, ruling out the coupling of paired alleles and the reduplication of germ cells and ruling in chromosomal mechanisms (Darden 1991). Genes are linked because they ride along on chromosomes in meiotic mechanisms. In immunology, the working entities in clonal selection were at first hypothesized to be self-replicating protein molecules but were later found to be self-reproducing immune cells (Darden 2006, Chapter 8). These two examples show that biologists do not always discover working entities in mechanisms by going to a smaller size level; sometimes the operative units are intermediate or larger than at first hypothesized: not genes but chromosomes, not molecules but cells. (2008, p. 961) 18
    19. 19. Causal assessmentThe (in)famousRusso-Williamson Thesis To establish a causal claim we typically need evidence of mechanisms and of difference-makingAn epistemological thesis aboutevidence for causal claimsFirst formulated for the health sciences,but can be extended to other sciences See however criticisms in the literature 19
    20. 20. Arguments for RWTMedical practice (IARC)History of medicine (Semmelweis)Epidemiology guidelines (Hill) 20
    21. 21. 6EVIDENCE OF MECHANISMS 21
    22. 22. “Disambiguating RWT”Evidence of difference-makingEvidence ofmechanismsPlausible mechanisms, rather than confirmedMethods generating the evidence vs evidence itselfDifference-making / Mechanisms A conceptual distinction In practice, highly intertwined 22
    23. 23. 7MECHANISMS AND REASONING 23
    24. 24. Howick: Mechanistic reasoning: involves an inference from mechanisms to claims that an intervention produces a patient-relevant outcome. Such reasoning will involve an inferential chain linking the intervention (such as antiarrhythmic drugs) with a clinical outcome. (2011, p.128) […] If, as Russo and Williamson appear to argue, mechanistic reasoning is required to establish causal claims, then it is reasonable to doubt the causal claim supported by strong comparative clinical studies. […] My argument is that mechanistic reasoning is not necessary to establish causal claims. (p.131) 24
    25. 25. Spot the odd-man outCausal assessment is based on evidence;The evidence required concerns: Mechanisms Difference makingMechanistic reasoning Inferential Not just about linking interventions and clinical outcomes 25
    26. 26. Nota bene …Knowledge of mechanisms is never ‘complete’Evidence is never ‘necessary’The epistemological basis of causal assessment does not always coincide with reasons for action 26
    27. 27. 8PLURALISM AND MONISM 27
    28. 28. Conceptual pluralism and monismEvidentialpluralism, conceptual monism From RWT to the epistemic theory Information theory? An account of production 28
    29. 29. 9PRACTICAL (SCIENTIFIC) USE 29
    30. 30. Mechanisms in the evidence hierarchyThe evidence hierarchy: the pillar of EBMThe role of mechanisms (from top to bottom)‘Reinforced concrete’ 30
    31. 31. Check out MatEH 31
    32. 32. DiagnosisMedical diagnosisDiagnosis of dysfunction in organisational science Enterprise Engineering and CIAO! network Cooperation & Interoperability - Architecture & Ontology 32
    33. 33. CIAO! network 33
    34. 34. Conceptualisation‘EnviroGenomarkers’ Project Mapping the evolution of biomarkers from exposure to early clinical changes to disease developmentA combination of processes and mechanisms 34
    35. 35. EnviroGenomarkers project 35
    36. 36. To sum up and conclude 36
    37. 37. Mechanisms: a (hot) field in phil sciReasons develop the field Mechanisms in contextsA growing interest No mechanisms in isolationImportant philosophical distinctions No panaceaGreat applicability to the Sharpening a conceptual sciences tool for a better science 37
    38. 38. 38

    ×