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Philosophy of Science — Key Points

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1. Central questions - What distinguishes science from non-science? (Demarcation problem) - How do scientific theories explain and predict phenomena? - What is the nature of scientific reasoning (induction, deduction, abduction)? - How do observation and theory interact (theory-ladenness of observation)? - What is the status of scientific knowledge (realism vs. anti-realism)? 2. Major positions - Scientific Realism: Best scientific theories approximately truthfully describe unobservable entities (Putnam, Boyd). - Instrumentalism/Anti-Realism: Theories are tools for prediction, not necessarily true descriptions (van Fraassen). - Constructivism and Social Epistemology: Scientific knowledge is shaped by social processes, values, and institutions (Kuhn, Latour). - Structuralism and Model-Based Views: Science advances via models and structures rather than literal true statements (Suppe, Cartwright). 3. Methodology and reasoning - Induction: Generalizing from observations—problem of justifying induction (Hume). - Falsificationism: Popper’s idea that theories are scientific if falsifiable; emphasizes bold conjectures and refutations. - Bayesianism: Probabilistic updating of belief based on evidence. - Lakatos’ Research Programmes: Science progresses through competing research programmes with heuristics and protective belts. 4. Explanation and laws - Covering-law model: Explanations subsume phenomena under general laws (Hempel). - Causal/mechanistic accounts: Explanations cite causes or mechanisms producing phenomena (Salmon, Craver). - Pragmatic and pluralist views: Multiple types of explanation depending on context. 5. Values, objectivity, and ethics - Science aims for objectivity, but choices about methods, significance, and application involve epistemic and non-epistemic values. - Responsible research requires transparency, reproducibility, and ethical reflection. 6. Contemporary issues - Replication crisis and reliability of findings. - Role of models, simulations, and big data. - Science policy, public trust, and science communication. Further reading (concise) - Peter Godfrey-Smith, Theory and Reality (2003) - Karl Popper, The Logic of Scientific Discovery (1959) - Thomas Kuhn, The Structure of Scientific Revolutions (1962) - Bas van Fraassen, The Scientific Image (1980) If you want, I can explain any one of these points in more detail or compare specific positions (e.g., realism vs. van Fraassen).

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Covering-Law Model (Hempel)

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The covering-law model, chiefly developed by Carl Hempel, explains how scientific explanations work by showing that the event or phenomenon to be explained (the explanandum) is logically or probabilistically deduced from general laws and specific circumstances (the explanans). In the deductive-nomological (D-N) version, an explanation takes the form of a valid deduction: given at least one general law and relevant initial conditions, the occurrence follows necessarily. The inductive-statistical (I-S) version handles probabilistic cases by showing that the explanans renders the explanandum highly probable rather than logically certain. Key features - Subsumption: Explaining means subsuming a phenomenon under general laws—“this happened because it falls under this law plus these conditions.” - Logical structure: Explanations are judged by logical relations (deduction or probabilistic support), not by causal storytelling. - Explanatory asymmetry: The model had trouble with cases (e.g., flagpole shadow) where deduction works both ways but only one is explanatory; Hempel and later commentators addressed such issues with added conditions (e.g., lawlikeness, relevance). - Limitations: Critics point out problems with relevance, singular causal explanations, and the role of mechanisms; alternative accounts (causal, mechanistic, unificationist) arose in response. Sources: Hempel, C. G. (1965) “Aspects of Scientific Explanation”; Salmon, W. C. (1984) Scientific Explanation and the Causal Structure of the World.

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