|
|||
 |
|||
|
|
|
|
|
|||
 |
|||
|
|
|
|
  A Metaphysics for Scientific Realism by Anjan Chakravartty | ||||
 | Sweeping, Informed, Bravo! A Metaphysics for Scientific Realism Knowing the Unobservable Anjan Chakravartty (Cambridge University Press 2007) From the Table of Contents: Part I Scientific realism today 1 Realism and antirealism; metaphysics and empiricism 1.1 The trouble with common sense 1.2 A conceptual taxonomy 1.3 Metaphysics, empiricism, and scientific knowledge 1.4 The rise of stance empiricism 1.5 The fall of the critique of metaphysics 2 Selective skepticism: entity realism, structural realism, semirealism 2.1 The entities are not alone 2.2 Lessons from epistemic structuralism 2.3 Semirealism (or: how to be a sophisticated realist) 2.4 Optimistic and pessimistic inductions on past science 2.5 The minimal interpretation of structure 3 Properties, particulars, and concrete structures 3.1 Inventory: what realists know 3.2 Mutually entailed particulars and structures 3.3 Ontic structuralism: farewell to objects? 3.4 Ontological theory change 3.5 Return of the motley particulars Part II Metaphysical foundations 4 Causal realism and causal processes 4.1 Causal connections and de re necessity 4.2 Is causal realism incoherent? 4.3 A first answer: relations between events 4.4 A better answer: causal processes 4.5 Processes for empiricists 5 Dispositions, property identity, and laws of nature 5.1 The causal property identity thesis 5.2 Property naming and necessity 5.3 Objections: epistemic and metaphysical 5.4 Vacuous laws and the ontology of causal properties 5.5 Causal laws, ceteris paribus 6 Sociability: natural and scientific kinds 6.1 Law statements and the role of kinds 6.2 Essences and clusters: two kinds of kinds 6.3 Clusters and biological species concepts 6.4 Sociability (or: how to make kinds with properties) 6.5 Beyond objectivity, subjectivity, and promiscuity Part III Theory meets world 7 Representing and describing: theories and models 7.1 Descriptions, and non-linguistic representations 7.2 Representing via abstraction and idealization 7.3 Extracting information from models 7.4 The inescapability of correspondence 7.5 Approximation and geometrical structures 8 Approximate truths about approximate truth 8.1 Knowledge in the absence of truth simpliciter 8.2 Measuring “truth-likeness” 8.3 Truth as a comparator for art and science 8.4 Depiction versus denotation; description versus reference 8.5 Products versus production; theories and models versus practice ~~~~~~~~ See also here. | |||
| ||||
 |
 |
|
 |
|
