of science • Focus on the “context of justi fi cation” • Scienti fi c knowledge is characterized not by how it is discovered/conceived • but rather by how it is justi fi ed: - Objective evidence - Logical reasoning (e.g. HD method) - Statistical methods (Bayesian or Frequentist) • The con fi rmatory view of science • Goal: accumulation of con fi rmed hypotheses
in which • each agent makes observation • updates her internal representation • writes a paper as a sample from • reviewer assesses based on his • if accepted, it is incorporated into the global posterior distribution • This whole process represents the Metropolis-Hasting algorithm for approximating the true posterior k o q(zk |o) w q(w|zk) l w q(w|zl) q(w|o) p(w|o) o q(zk |o) q(w|zk) q(w|zl) q(w|o) p(w|o) ≈
(Longino, Kitcher) • The received view • Scienti fi c method is practiced by a single individual. • Objectivity is warranted by individual scientists’ following the method. • Social objectivity (Longino 1990, Kitcher 1993) • “The objectivity of scienti fi c inquiry is a consequence of this inquiry’s being a social, and not an individual, enterprise (Longino, p. 67).” - Intersubjective criticisms (peer review, replications) - Heterogeneity & diversity - Situatedness (di ff erent motivations, agenda, and biases)
CPC-MS as a model of scienti fi c interactions • Paper-writing → Review → Incorporation into the posterior • Convergence without consensus • Convergence of the posterior happens even if - individual scientists disagree each other, i.e., - they have incorrect posterior, • Diversity and openness promote convergence • Ergodicity of Markov Chain → will explore all possibilities in the long run q(w|o) ≈ p(w|o) q(zk |o) ≠ q(zl |o) q(zk |o) ≠ p(zk |o)
CPC-MS as a model of scienti fi c interactions • Paper-writing → Review → Incorporation into the posterior • Convergence without consensus • Convergence of the posterior happens even if - individual scientists disagree each other, i.e., - they have incorrect posterior, • Diversity and openness promote convergence • Ergodicity of Markov Chain → will explore all possibilities in the long run q(w|o) ≈ p(w|o) q(zk |o) ≠ q(zl |o) q(zk |o) ≠ p(zk |o)
c progress • Progress = accumulation of (con fi rmed) knowledge? • Di ffi culties 1. Incommensurability between scienti fi c revolutions (Kuhn) • No common standard between old/new paradigm. • How to say that the new paradigm is “better” than the old one? 2. Pessimistic induction • Many scienti fi c theories ended up being refuted. So no accumulation after all?
tools” • Received view: scienti fi c methods as algorithms to truth • Used by each individual scientist • Bring about objective conclusions when used properly • Generative view: scienti fi c methods as communication tools • Material and methods: clarify the assumptions/logic • Statistics: allows peer-reviewers to judge the quality of evidence • → communication platform for scienti fi c exchange
CPC-MS as a model of Social Objectivity • Diversity promotes convergence w/o consensus 2. Scienti fi c Progress • Progress in terms of predictive performance, even between di ff erent paradigms 3. Scienti fi c Methodology • Statistics as “communication tools” that facilitate the MHNG