Combining Texts

All the ideas for 'On the Question of Absolute Undecidability', 'Virtues of the Mind' and 'Inference to the Best Explanation (2nd)'

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96 ideas

1. Philosophy / A. Wisdom / 1. Nature of Wisdom
Unlike knowledge, wisdom cannot be misused [Zagzebski]
1. Philosophy / A. Wisdom / 2. Wise People
Wisdom is the property of a person, not of their cognitive state [Zagzebski, by Whitcomb]
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]
2. Reason / D. Definition / 2. Aims of Definition
Precision is only one of the virtues of a good definition [Zagzebski]
2. Reason / E. Argument / 1. Argument
Objection by counterexample is weak, because it only reveals inaccuracies in one theory [Zagzebski]
4. Formal Logic / F. Set Theory ST / 1. Set Theory
Mathematical set theory has many plausible stopping points, such as finitism, and predicativism [Koellner]
'Reflection principles' say the whole truth about sets can't be captured [Koellner]
5. Theory of Logic / K. Features of Logics / 5. Incompleteness
We have no argument to show a statement is absolutely undecidable [Koellner]
6. Mathematics / A. Nature of Mathematics / 5. The Infinite / i. Cardinal infinity
There are at least eleven types of large cardinal, of increasing logical strength [Koellner]
6. Mathematics / B. Foundations for Mathematics / 4. Axioms for Number / d. Peano arithmetic
PA is consistent as far as we can accept, and we expand axioms to overcome limitations [Koellner]
6. Mathematics / B. Foundations for Mathematics / 4. Axioms for Number / g. Incompleteness of Arithmetic
Arithmetical undecidability is always settled at the next stage up [Koellner]
11. Knowledge Aims / A. Knowledge / 2. Understanding
Understanding is not mysterious - it is just more knowledge, of causes [Lipton]
Modern epistemology is too atomistic, and neglects understanding [Zagzebski]
Epistemology is excessively atomic, by focusing on justification instead of understanding [Zagzebski]
11. Knowledge Aims / A. Knowledge / 3. Value of Knowledge
Truth is valuable, but someone knowing the truth is more valuable [Zagzebski]
11. Knowledge Aims / A. Knowledge / 4. Belief / d. Cause of beliefs
Some beliefs are fairly voluntary, and others are not at all so [Zagzebski]
11. Knowledge Aims / A. Knowledge / 5. Aiming at Truth
Knowledge either aims at a quantity of truths, or a quality of understanding of truths [Zagzebski]
13. Knowledge Criteria / A. Justification Problems / 2. Justification Challenges / b. Gettier problem
For internalists Gettier situations are where internally it is fine, but there is an external mishap [Zagzebski]
Gettier problems are always possible if justification and truth are not closely linked [Zagzebski]
We avoid the Gettier problem if the support for the belief entails its truth [Zagzebski]
Gettier cases arise when good luck cancels out bad luck [Zagzebski]
13. Knowledge Criteria / B. Internal Justification / 1. Epistemic virtues
Intellectual virtues are forms of moral virtue [Zagzebski]
A reliable process is no use without the virtues to make use of them [Zagzebski]
Intellectual and moral prejudice are the same vice (and there are other examples) [Zagzebski]
We can name at least thirteen intellectual vices [Zagzebski]
A justified belief emulates the understanding and beliefs of an intellectually virtuous person [Zagzebski]
13. Knowledge Criteria / B. Internal Justification / 3. Evidentialism / a. Evidence
How do we distinguish negative from irrelevant evidence, if both match the hypothesis? [Lipton]
13. Knowledge Criteria / C. External Justification / 3. Reliabilism / b. Anti-reliabilism
Epistemic perfection for reliabilism is a truth-producing machine [Zagzebski]
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]
Bayes is too liberal, since any logical consequence of a hypothesis confirms it [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]
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]
16. Persons / C. Self-Awareness / 2. Knowing the Self
The self is known as much by its knowledge as by its action [Zagzebski]
18. Thought / A. Modes of Thought / 3. Emotions / d. Emotional feeling
The feeling accompanying curiosity is neither pleasant nor painful [Zagzebski]
20. Action / C. Motives for Action / 1. Acting on Desires
Motives involve desires, but also how the desires connect to our aims [Zagzebski]
22. Metaethics / A. Ethics Foundations / 1. Nature of Ethics / d. Ethical theory
Modern moral theory concerns settling conflicts, rather than human fulfilment [Zagzebski]
22. Metaethics / C. The Good / 1. Goodness / i. Moral luck
Moral luck means our praise and blame may exceed our control or awareness [Zagzebski]
22. Metaethics / C. The Good / 2. Happiness / b. Eudaimonia
Nowadays we doubt the Greek view that the flourishing of individuals and communities are linked [Zagzebski]
23. Ethics / C. Virtue Theory / 1. Virtue Theory / a. Nature of virtue
Virtue theory is hopeless if there is no core of agreed universal virtues [Zagzebski]
A virtue must always have a corresponding vice [Zagzebski]
Eight marks distingush skills from virtues [Zagzebski, by PG]
Virtues are deep acquired excellences of persons, which successfully attain desire ends [Zagzebski]
Every moral virtue requires a degree of intelligence [Zagzebski]
23. Ethics / C. Virtue Theory / 1. Virtue Theory / c. Particularism
Virtue theory can have lots of rules, as long as they are grounded in virtues and in facts [Zagzebski]
23. Ethics / C. Virtue Theory / 2. Elements of Virtue Theory / j. Unity of virtue
We need phronesis to coordinate our virtues [Zagzebski]
23. Ethics / C. Virtue Theory / 3. Virtues / a. Virtues
For the virtue of honesty you must be careful with the truth, and not just speak truly [Zagzebski]
23. Ethics / C. Virtue Theory / 3. Virtues / d. Courage
The courage of an evil person is still a quality worth having [Zagzebski]
26. Natural Theory / C. Causation / 9. General Causation / c. Counterfactual causation
Counterfactual causation makes causes necessary but not sufficient [Lipton]