The Material Theory
of Induction
JOHN D. NORTON
2016, 2017
Contents
Drafts are available for many chapters as indicated below.
1. The Material Theory of Induction Stated and Illustrated  draft 
Inductive inferences are not warranted by
conformity with some universally applicable formal schema. They
are warranted by background facts. The theory is illustrated with
Marie Curie's inductive inference over the crystallographic
properties of Radium Chloride. 

2. What Powers Inductive Inference?  draft 
The principal arguments for the material theory
are given. Any particular inductive inference can fail reliably if
we try it in a universe hostile to it. That the universe is
hospitable to the inference is a contingent, factual matter and is
the fact that warrants it. The material theory asserts that there are no universal rules of inductive inference. All induction is local.Chapters 38 will show how popular and apparently universal rules of inductive inference are defeasible and that their warrants in individual domains are best understood as deriving from particular background facts. 

3. Replicability of Experiment  draft 
There is no universal inductive principle in science formulated in terms of replicability of experiment. Replication is not guaranteed to have inductive force. When it does, the force derives from background facts peculiar to the case at hand.  
4. Analogy  draft 
Efforts to characterize good analogical
inferences by their form have collapsed under the massive weight
of the endless complexity needed to formulate a viable, general
rule. For scientists, analogies are facts not argument forms,
which fits nicely with the material view. 

5. Epistemic Virtues and Epistemic Values: A Skeptical Critique  draft 
Talk of epistemic values in inference misleads
by suggesting that our preference for simpler theories is akin to
a free choice, such as being a vegetarian. The better word is
criterion, since they are nor freely chose, but must prove their
mettle in guiding us to the truth. 

6. Simplicity as a Surrogate  draft 
There is no viable principle that attaches
simpler hypotheses to the truth. Appeals to simplicity are
shortcuts that disguise more complicated appeals to background
facts. 

7. Simplicity in Model Selection  draft 
Statistical techniques, such as the Akaike Information Criterion, do not vindicate appeals to simplicity as general principle. AIC depends on certain strong, background assumptions independent of simplicity. We impose a simplicity interpretation on the formula it produces.  
8. Inference to the Best Explanation: The General Account  draft 
9. Inference to the Best Explanation: Examples  draft 
There is no clearly defined relation of
explanation that confers special inductive support on some
hypotheses or theories. The important, canonical examples of IBE
can be accommodated better by simpler schemes involving background
facts. The successful hypotheses or theories accommodate the
evidence. The major burden in real cases in science is to show
that competing accounts fail, either by contradicting the evidence
or taking on evidential debt. Chapters 914 address Bayesian confirmation theory, which has become the default account of inductive inference in philosophy of science, in spite of its weaknesses. Chapters 9 and 10 address general issues. Chapters 1114 display systems in which probabilistic representation of inductive strengths of support fails. 

10. Why Not Bayes?  draft 
While probabilistic analysis of inductive
inference can be very successful in certain domains, it must fail
as the universal logic of inductive inference. For an inductive
logic must constrains systems beyond merely logical consistency.
The resulting contingent restriction will only obtain in some
domains. Proofs of the necessity of probabilistic accounts fail
since they require assumptions as strong as the result they seek
to establish. 

11. Circularity in the Scoring Rule Vindication of Probabilities  draft 
This chapter provides an extended illustration
of the circularity in demonstrations of the necessity of
probabilities. The scoring rule approach employs only the notion
of accuracy and claims that probabilistic credences dominate. This
chapter shows that accuracy provides little. The result really
comes from an unjustified fine tuning of the scoring rule. 

12. Incompleteness of All Calculi of Inductive Inference  coming 
A Bayesian analysis is always incomplete in
that substantial inductive content must always be provided to the
analysis externally through its prior probabilities. This chapter
reviews and illustrates a proof that all calculi of inductive
inference, not just a probabilistic one, exhibit some form of
incompleteness. 

13. Infinite Lottery Machines  draft 
Such machines choose among a countable infinite
of outcomes without favor. While the example is used to impugn
countable additivity, it actually also precludes even finite
additivity. 

14. Indeterministic Physical Systems  draft 
A collection of indeterministic systems are
described whose indeterminism poses problems in inductive
inference. They cannot be solved by representing strengths of
inductive support as probabilities, unless one alters the problem
posed. 

15. Nonmeasurable Outcomes  coming 
Probabilistically nonmeasureable outcomes pose
problems for a probabilistic inductive logic. August 14, 2017. An earlier draft chapter has been removed since its analysis was based on an incorrect identification of a nonmeasurable outcome. Apologies for any confusions. 

16. A Quantum Inductive Logic  draft 
While the examples of Chapters 1113 were
simplified, this chapter proposes that there is nonprobabilistic
inductive logic native to a real science, quantum mechanics. 

17. Conclusion  coming 