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E-grāmata: Probabilistic Knowledge

3.90/5 (10 ratings by Goodreads)
(Associate Professor of Philosophy, University of Michigan, Ann Arbor)
  • Formāts: 224 pages
  • Izdošanas datums: 16-Feb-2018
  • Izdevniecība: Oxford University Press
  • Valoda: eng
  • ISBN-13: 9780192510594
  • Formāts - EPUB+DRM
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  • Formāts: 224 pages
  • Izdošanas datums: 16-Feb-2018
  • Izdevniecība: Oxford University Press
  • Valoda: eng
  • ISBN-13: 9780192510594

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Traditional philosophical discussions of knowledge have focused on the epistemic status of full beliefs. Sarah Moss argues that in addition to full beliefs, credences can constitute knowledge. For instance, your 0.4 credence that it is raining outside can constitute knowledge, in just the same way that your full beliefs can. In addition, you can know that it might be raining, and that if it is raining then it is probably cloudy, where this knowledge is not knowledge of propositions, but of probabilistic contents.

The notion of probabilistic content introduced in this book plays a central role not only in epistemology, but in the philosophy of mind and language as well. Just as tradition holds that you believe and assert propositions, you can believe and assert probabilistic contents. Accepting that we can believe, assert, and know probabilistic contents has significant consequences for many philosophical debates, including debates about the relationship between full belief and credence, the semantics of epistemic modals and conditionals, the contents of perceptual experience, peer disagreement, pragmatic encroachment, perceptual dogmatism, and transformative experience. In addition, accepting probabilistic knowledge can help us discredit negative evaluations of female speech, explain why merely statistical evidence is insufficient for legal proof, and identify epistemic norms violated by acts of racial profiling. Hence the central theses of this book not only help us better understand the nature of our own mental states, but also help us better understand the nature of our responsibilities to each other.

Recenzijas

Essential reading for philosophers of language, semanticists, and formal epistemologists. . . . Probabilistic Knowledge offers a persuasive case for a radical revision of some foundational ideas about the nature of content and communication. . . . rich and rewarding. * Daniel Greco, Journal of Philosophy * The title concept of this book, probabilistic knowledge, involves a radical revision of some central ideas of epistemology. But it ends up providing a more unified account of many phenomena of recent interest. Philosophers with an interest in the formal semantics of conditionals or epistemic modals, and epistemologists working on contextualism or the interaction of credence and belief, should probably read most or all of this book. And many other philosophers should also find a copy. * Kenny Easwaran, Notre Dame Philosophical Reviews *

Papildus informācija

Winner of Winner of the APA 2020 Sanders Book Prize.
Preface ix
1 The case for probabilistic contents
1(19)
1.1 Probabilistic beliefs
1(2)
1.2 An argument for probabilistic contents of belief
3(7)
1.3 The roles played by contents of belief
10(4)
1.4 Full beliefs
14(1)
1.5 Alternative roles for contents of belief
15(5)
2 The case for probabilistic assertion
20(18)
2.1 Familiar arguments against propositional contents of assertion
20(5)
2.2 Foundational arguments for probabilistic contents of assertion
25(4)
2.3 Modeling communication
29(2)
2.4 Epistemic modals and indicative conditionals
31(2)
2.5 A test battery for probabilistic content
33(5)
3 Epistemic modals and probability operators
38(26)
3.1 Motivations for my semantics
38(3)
3.2 Embedded epistemic vocabulary
41(4)
3.3 Challenges for other theories
45(5)
3.4 A semantics for epistemic modals and probability operators
50(3)
3.5 A semantics for simple sentences
53(5)
3.6 The relationship between credence and full belief
58(6)
4 Indicative conditionals
64(21)
4.1 Probabilities of conditionals as conditional probabilities
64(2)
4.2 A semantics for conditionals
66(3)
4.3 Why probabilities of conditionals are not conditional probabilities
69(5)
4.4 A semantics for other logical operators
74(6)
4.5 The pragmatics of epistemic vocabulary
80(5)
5 The case for probabilistic knowledge
85(32)
5.1 The thesis that probabilistic beliefs can be knowledge
85(2)
5.2 Testimony
87(2)
5.3 Perception
89(3)
5.4 Arguments for probabilistic contents of experience
92(7)
5.5 Other sources of knowledge
99(2)
5.6 Justified true belief without knowledge
101(3)
5.7 Traditional theories of knowledge
104(5)
5.8 An alternative mental state?
109(2)
5.9 Applications
111(6)
6 Factivity
117(14)
6.1 Alternatives to probabilistic knowledge?
117(3)
6.2 The contents of knowledge ascriptions
120(2)
6.3 Frequendy asked questions
122(4)
6.4 Relativism
126(3)
6.5 Objective chance
129(2)
7 Skepticism
131(27)
7.1 A skeptical puzzle
131(1)
7.2 The argument from inconsistency
131(2)
7.3 The argument from closure
133(7)
7.4 The argument from disjunction
140(6)
7.5 The argument from safety
146(12)
8 Knowledge and belief
158(23)
8.1 The knowledge norm of belief
158(2)
8.2 Peer disagreement
160(4)
8.3 Applying the knowledge norm of belief
164(4)
8.4 Statistical inference
168(6)
8.5 Responses to skepticism about perceptual knowledge
174(7)
9 Knowledge and action
181(20)
9.1 Knowledge norms of action
181(3)
9.2 Addressing objections
184(4)
9.3 Applying knowledge norms of action
188(4)
9.4 Pragmatic encroachment
192(2)
9.5 Transformative experience
194(7)
10 Knowledge and persons
201(30)
10.1 Statistical evidence
201(7)
10.2 An account of legal proof
208(8)
10.3 Applying knowledge standards of proof
216(4)
10.4 Racial and other profiling
220(5)
10.5 Applying the rule of consideration
225(6)
Appendix: A formal semantics for epistemic vocabulary
231(12)
A.1 Background
231(1)
A.2 Epistemic modals and probability operators
231(3)
A.3 Simple sentences
234(1)
A.4 Indicative conditionals
234(3)
A.5 Other logical operators
237(6)
References 243(18)
Index 261
Sarah Moss is Associate Professor of Philosophy at the University of Michigan, Ann Arbor. She received her A.B. in Mathematics from Harvard University and her B.Phil. in Philosophy from Oxford University, where she studied as a Marshall Scholar. She received her Ph.D. in Philosophy with a minor in Linguistics from MIT in 2009.