Combining Texts

All the ideas for 'Inference to the Best Explanation (2nd)', 'A Puzzle Concerning Matter and Form' and 'The Boundary Stones of Thought'

expand these ideas     |    start again     |     specify just one area for these texts


94 ideas

1. Philosophy / E. Nature of Metaphysics / 6. Metaphysics as Conceptual
Logic doesn't have a metaphysical basis, but nor can logic give rise to the metaphysics [Rumfitt]
2. Reason / A. Nature of Reason / 4. Aims of Reason
Good inference has mechanism, precision, scope, simplicity, fertility and background fit [Lipton]
2. Reason / B. Laws of Thought / 4. Contraries
Contrary pairs entail contradictions; one member entails negation of the other [Lipton]
3. Truth / A. Truth Problems / 1. Truth
The idea that there are unrecognised truths is basic to our concept of truth [Rumfitt]
3. Truth / B. Truthmakers / 7. Making Modal Truths
'True at a possibility' means necessarily true if what is said had obtained [Rumfitt]
4. Formal Logic / B. Propositional Logic PL / 1. Propositional Logic
Semantics for propositions: 1) validity preserves truth 2) non-contradition 3) bivalence 4) truth tables [Rumfitt]
4. Formal Logic / D. Modal Logic ML / 3. Modal Logic Systems / h. System S5
'Absolute necessity' would have to rest on S5 [Rumfitt]
4. Formal Logic / E. Nonclassical Logics / 2. Intuitionist Logic
It is the second-order part of intuitionistic logic which actually negates some classical theorems [Rumfitt]
Intuitionists can accept Double Negation Elimination for decidable propositions [Rumfitt]
4. Formal Logic / F. Set Theory ST / 1. Set Theory
Most set theorists doubt bivalence for the Continuum Hypothesis, but still use classical logic [Rumfitt]
4. Formal Logic / F. Set Theory ST / 4. Axioms for Sets / a. Axioms for sets
The iterated conception of set requires continual increase in axiom strength [Rumfitt]
4. Formal Logic / F. Set Theory ST / 4. Axioms for Sets / b. Axiom of Extensionality I
A set may well not consist of its members; the empty set, for example, is a problem [Rumfitt]
A set can be determinate, because of its concept, and still have vague membership [Rumfitt]
4. Formal Logic / F. Set Theory ST / 4. Axioms for Sets / g. Axiom of Powers VI
If the totality of sets is not well-defined, there must be doubt about the Power Set Axiom [Rumfitt]
5. Theory of Logic / A. Overview of Logic / 1. Overview of Logic
Logic is higher-order laws which can expand the range of any sort of deduction [Rumfitt]
5. Theory of Logic / A. Overview of Logic / 6. Classical Logic
The case for classical logic rests on its rules, much more than on the Principle of Bivalence [Rumfitt]
Classical logic rules cannot be proved, but various lines of attack can be repelled [Rumfitt]
If truth-tables specify the connectives, classical logic must rely on Bivalence [Rumfitt]
5. Theory of Logic / B. Logical Consequence / 1. Logical Consequence
Logical consequence is a relation that can extended into further statements [Rumfitt]
5. Theory of Logic / B. Logical Consequence / 3. Deductive Consequence |-
Normal deduction presupposes the Cut Law [Rumfitt]
5. Theory of Logic / D. Assumptions for Logic / 1. Bivalence
When faced with vague statements, Bivalence is not a compelling principle [Rumfitt]
5. Theory of Logic / E. Structures of Logic / 2. Logical Connectives / a. Logical connectives
In specifying a logical constant, use of that constant is quite unavoidable [Rumfitt]
5. Theory of Logic / H. Proof Systems / 4. Natural Deduction
Introduction rules give deduction conditions, and Elimination says what can be deduced [Rumfitt]
5. Theory of Logic / I. Semantics of Logic / 3. Logical Truth
Logical truths are just the assumption-free by-products of logical rules [Rumfitt]
5. Theory of Logic / K. Features of Logics / 10. Monotonicity
Monotonicity means there is a guarantee, rather than mere inductive support [Rumfitt]
6. Mathematics / A. Nature of Mathematics / 3. Nature of Numbers / e. Ordinal numbers
Maybe an ordinal is a property of isomorphic well-ordered sets, and not itself a set [Rumfitt]
6. Mathematics / A. Nature of Mathematics / 5. The Infinite / k. Infinitesimals
Infinitesimals do not stand in a determinate order relation to zero [Rumfitt]
6. Mathematics / B. Foundations for Mathematics / 1. Foundations for Mathematics
Cantor and Dedekind aimed to give analysis a foundation in set theory (rather than geometry) [Rumfitt]
8. Modes of Existence / C. Powers and Dispositions / 4. Powers as Essence
The possible Aristotelian view that forms are real and active principles is clearly wrong [Fine,K, by Pasnau]
9. Objects / B. Unity of Objects / 3. Unity Problems / e. Vague objects
An object that is not clearly red or orange can still be red-or-orange, which sweeps up problem cases [Rumfitt]
The extension of a colour is decided by a concept's place in a network of contraries [Rumfitt]
10. Modality / A. Necessity / 5. Metaphysical Necessity
Metaphysical modalities respect the actual identities of things [Rumfitt]
10. Modality / A. Necessity / 6. Logical Necessity
S5 is the logic of logical necessity [Rumfitt]
10. Modality / B. Possibility / 1. Possibility
Since possibilities are properties of the world, calling 'red' the determination of a determinable seems right [Rumfitt]
If two possibilities can't share a determiner, they are incompatible [Rumfitt]
10. Modality / E. Possible worlds / 1. Possible Worlds / e. Against possible worlds
Possibilities are like possible worlds, but not fully determinate or complete [Rumfitt]
11. Knowledge Aims / A. Knowledge / 2. Understanding
Understanding is not mysterious - it is just more knowledge, of causes [Lipton]
Medieval logicians said understanding A also involved understanding not-A [Rumfitt]
13. Knowledge Criteria / B. Internal Justification / 3. Evidentialism / a. Evidence
How do we distinguish negative from irrelevant evidence, if both match the hypothesis? [Lipton]
In English 'evidence' is a mass term, qualified by 'little' and 'more' [Rumfitt]
14. Science / A. Basis of Science / 1. Observation
The inference to observables and unobservables is almost the same, so why distinguish them? [Lipton]
14. Science / A. Basis of Science / 2. Demonstration
Inductive inference is not proof, but weighing evidence and probability [Lipton]
We infer from evidence by working out what would explain that evidence [Lipton]
14. Science / A. Basis of Science / 4. Prediction
It is more impressive that relativity predicted Mercury's orbit than if it had accommodated it [Lipton]
Predictions are best for finding explanations, because mere accommodations can be fudged [Lipton]
14. Science / B. Scientific Theories / 1. Scientific Theory
If we make a hypothesis about data, then a deduction, where does the hypothesis come from? [Lipton]
14. Science / C. Induction / 1. Induction
Induction is repetition, instances, deduction, probability or causation [Lipton]
14. Science / C. Induction / 3. Limits of Induction
Standard induction does not allow for vertical inferences, to some unobservable lower level [Lipton]
14. Science / C. Induction / 4. Reason in Induction
An inductive inference is underdetermined, by definition [Lipton]
We can argue to support our beliefs, so induction will support induction, for believers in induction [Lipton]
14. Science / C. Induction / 5. Paradoxes of Induction / b. Raven paradox
If something in ravens makes them black, it may be essential (definitive of ravens) [Lipton]
My shoes are not white because they lack some black essence of ravens [Lipton]
A theory may explain the blackness of a raven, but say nothing about the whiteness of shoes [Lipton]
We can't turn non-black non-ravens into ravens, to test the theory [Lipton]
To pick a suitable contrast to ravens, we need a hypothesis about their genes [Lipton]
14. Science / C. Induction / 6. Bayes's Theorem
Bayes seems to rule out prior evidence, since that has a probability of one [Lipton]
A hypothesis is confirmed if an unlikely prediction comes true [Lipton]
Bayes involves 'prior' probabilities, 'likelihood', 'posterior' probability, and 'conditionalising' [Lipton]
Explanation may be an important part of implementing Bayes's Theorem [Lipton]
Bayes is too liberal, since any logical consequence of a hypothesis confirms it [Lipton]
14. Science / D. Explanation / 1. Explanation / a. Explanation
Explanation may describe induction, but may not show how it justifies, or leads to truth [Lipton]
14. Science / D. Explanation / 1. Explanation / b. Aims of explanation
An explanation gives the reason the phenomenon occurred [Lipton]
An explanation is what makes the unfamiliar familiar to us [Lipton]
An explanation is what is added to knowledge to yield understanding [Lipton]
Seaching for explanations is a good way to discover the structure of the world [Lipton]
14. Science / D. Explanation / 2. Types of Explanation / b. Contrastive explanations
In 'contrastive' explanation there is a fact and a foil - why that fact, rather than this foil? [Lipton]
With too many causes, find a suitable 'foil' for contrast, and the field narrows right down [Lipton]
14. Science / D. Explanation / 2. Types of Explanation / c. Explanations by coherence
An explanation unifies a phenomenon with our account of other phenomena [Lipton]
14. Science / D. Explanation / 2. Types of Explanation / e. Lawlike explanations
Deduction explanation is too easy; any law at all will imply the facts - together with the facts! [Lipton]
We reject deductive explanations if they don't explain, not if the deduction is bad [Lipton]
Good explanations may involve no laws and no deductions [Lipton]
14. Science / D. Explanation / 2. Types of Explanation / f. Necessity in explanations
An explanation shows why it was necessary that the effect occurred [Lipton]
14. Science / D. Explanation / 2. Types of Explanation / g. Causal explanations
A cause may not be an explanation [Lipton]
To explain is to give either the causal history, or the causal mechanism [Lipton]
Mathematical and philosophical explanations are not causal [Lipton]
Explanations may be easier to find than causes [Lipton]
Causal inferences are clearest when we can manipulate things [Lipton]
14. Science / D. Explanation / 2. Types of Explanation / i. Explanations by mechanism
We want to know not just the cause, but how the cause operated [Lipton]
14. Science / D. Explanation / 2. Types of Explanation / l. Probabilistic explanations
To maximise probability, don't go beyond your data [Lipton]
14. Science / D. Explanation / 3. Best Explanation / a. Best explanation
Is Inference to the Best Explanation nothing more than inferring the likeliest cause? [Lipton]
Best Explanation as a guide to inference is preferable to best standard explanations [Lipton]
The 'likeliest' explanation is the best supported; the 'loveliest' gives the most understanding [Lipton]
IBE is inferring that the best potential explanation is the actual explanation [Lipton]
Finding the 'loveliest' potential explanation links truth to understanding [Lipton]
IBE is not passive treatment of data, but involves feedback between theory and data search [Lipton]
A contrasting difference is the cause if it offers the best explanation [Lipton]
We select possible explanations for explanatory reasons, as well as choosing among them [Lipton]
14. Science / D. Explanation / 3. Best Explanation / c. Against best explanation
Must we only have one explanation, and must all the data be made relevant? [Lipton]
Bayesians say best explanations build up an incoherent overall position [Lipton]
The best theory is boring: compare 'all planets move elliptically' with 'most of them do' [Lipton]
Best explanation can't be a guide to truth, because the truth must precede explanation [Lipton]
19. Language / A. Nature of Meaning / 4. Meaning as Truth-Conditions
We understand conditionals, but disagree over their truth-conditions [Rumfitt]
19. Language / F. Communication / 3. Denial
The truth grounds for 'not A' are the possibilities incompatible with truth grounds for A [Rumfitt]
26. Natural Theory / C. Causation / 9. General Causation / c. Counterfactual causation
Counterfactual causation makes causes necessary but not sufficient [Lipton]