Combining Philosophers

All the ideas for Reiss,J/Spreger,J, Kenneth Kunen and R Keefe / P Smith

unexpand these ideas     |    start again     |     specify just one area for these philosophers


37 ideas

2. Reason / A. Nature of Reason / 5. Objectivity
One view says objectivity is making a successful claim which captures the facts [Reiss/Sprenger]
     Full Idea: One conception of objectivity is that the facts are 'out there', and it is the task of scientists to discover, analyze and sytematize them. 'Objective' is a success word: if a claim is objective, it successfully captures some feature of the world.
     From: Reiss,J/Spreger,J (Scientific Objectivity [2014], 2)
     A reaction: This seems to describe truth, rather than objectivity. You can establish accurate facts by subjective means. You can be fairly objective but miss the facts. Objectivity is a mode of thought, not a link to reality.
An absolute scientific picture of reality must not involve sense experience, which is perspectival [Reiss/Sprenger]
     Full Idea: Sense experience is necessarily perspectival, so to the extent to which scientific theories are to track the absolute conception [of reality], they must describe a world different from sense experience.
     From: Reiss,J/Spreger,J (Scientific Objectivity [2014], 2.3)
     A reaction: This is a beautifully simple and interesting point. Even when you are looking at a tree, to grasp its full reality you probably need to close your eyes (which is bad news for artists).
Topic and application involve values, but can evidence and theory choice avoid them? [Reiss/Sprenger]
     Full Idea: There may be values involved in the choice of a research problem, the gathering of evidence, the acceptance of a theory, and the application of results. ...The first and fourth do involve values, but what of the second and third?
     From: Reiss,J/Spreger,J (Scientific Objectivity [2014], 3.1)
     A reaction: [compressed] My own view is that the danger of hidden distorting values has to be recognised, but it is then possible, by honest self-criticism, to reduce them to near zero. Sociological enquiry is different, of course.
The Value-Free Ideal in science avoids contextual values, but embraces epistemic values [Reiss/Sprenger]
     Full Idea: According to the Value-Free Ideal, scientific objectivity is characterised by absence of contextual values and by exclusive commitment to epistemic values in scientific reasoning.
     From: Reiss,J/Spreger,J (Scientific Objectivity [2014], 3.1)
     A reaction: This seems appealing, because it concedes that we cannot be value-free, without suggesting that we are unavoidably swamped by values. The obvious question is whether the two types of value can be sharply distinguished.
Value-free science needs impartial evaluation, theories asserting facts, and right motivation [Reiss/Sprenger]
     Full Idea: Three components of value-free science are Impartiality (appraising theories only by epistemic scientific standards), Neutrality (the theories make no value statements), and Autonomy (the theory is motivated only by science).
     From: Reiss,J/Spreger,J (Scientific Objectivity [2014], 3.3)
     A reaction: [They are summarising Hugh Lacey, 1999, 2002] I'm not sure why the third criterion matters, if the first two are met. If a tobacco company commissions research on cigarettes, that doesn't necessarily make the findings false or prejudiced.
Thermometers depend on the substance used, and none of them are perfect [Reiss/Sprenger]
     Full Idea: Thermometers assume the length of the fluid or gas is a function of temperature, and different substances yield different results. It was decided that different thermometers using the same substance should match, and air was the best, but not perfect.
     From: Reiss,J/Spreger,J (Scientific Objectivity [2014], 4.1)
     A reaction: [summarising Hasok Chang's research] This is a salutary warning that instruments do not necessarily solve the problem of objectivity, though thermometers do seem to be impersonal, and offer relative accuracy (i.e. ranking temperatures). Cf breathalysers.
4. Formal Logic / D. Modal Logic ML / 3. Modal Logic Systems / h. System S5
S5 collapses iterated modalities (◊□P→□P, and ◊◊P→◊P) [Keefe/Smith]
     Full Idea: S5 collapses iterated modalities (so ◊□P → □P, and ◊◊P → ◊P).
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §5)
     A reaction: It is obvious why this might be controversial, and there seems to be a general preference for S4. There may be confusions of epistemic and ontic (and even semantic?) possibilities within a single string of modalities.
4. Formal Logic / F. Set Theory ST / 4. Axioms for Sets / b. Axiom of Extensionality I
Extensionality: ∀x ∀y (∀z (z ∈ x ↔ z ∈ y) → x = y) [Kunen]
     Full Idea: Axiom of Extensionality: ∀x ∀y (∀z (z ∈ x ↔ z ∈ y) → x = y). That is, a set is determined by its members. If every z in one set is also in the other set, then the two sets are the same.
     From: Kenneth Kunen (Set Theory [1980], §1.5)
4. Formal Logic / F. Set Theory ST / 4. Axioms for Sets / c. Axiom of Pairing II
Pairing: ∀x ∀y ∃z (x ∈ z ∧ y ∈ z) [Kunen]
     Full Idea: Axiom of Pairing: ∀x ∀y ∃z (x ∈ z ∧ y ∈ z). Any pair of entities must form a set.
     From: Kenneth Kunen (Set Theory [1980], §1.6)
     A reaction: Repeated applications of this can build the hierarchy of sets.
4. Formal Logic / F. Set Theory ST / 4. Axioms for Sets / d. Axiom of Unions III
Union: ∀F ∃A ∀Y ∀x (x ∈ Y ∧ Y ∈ F → x ∈ A) [Kunen]
     Full Idea: Axiom of Union: ∀F ∃A ∀Y ∀x (x ∈ Y ∧ Y ∈ F → x ∈ A). That is, the union of a set (all the members of the members of the set) must also be a set.
     From: Kenneth Kunen (Set Theory [1980], §1.6)
4. Formal Logic / F. Set Theory ST / 4. Axioms for Sets / f. Axiom of Infinity V
Infinity: ∃x (0 ∈ x ∧ ∀y ∈ x (S(y) ∈ x) [Kunen]
     Full Idea: Axiom of Infinity: ∃x (0 ∈ x ∧ ∀y ∈ x (S(y) ∈ x). That is, there is a set which contains zero and all of its successors, hence all the natural numbers. The principal of induction rests on this axiom.
     From: Kenneth Kunen (Set Theory [1980], §1.7)
4. Formal Logic / F. Set Theory ST / 4. Axioms for Sets / g. Axiom of Powers VI
Power Set: ∀x ∃y ∀z(z ⊂ x → z ∈ y) [Kunen]
     Full Idea: Power Set Axiom: ∀x ∃y ∀z(z ⊂ x → z ∈ y). That is, there is a set y which contains all of the subsets of a given set. Hence we define P(x) = {z : z ⊂ x}.
     From: Kenneth Kunen (Set Theory [1980], §1.10)
4. Formal Logic / F. Set Theory ST / 4. Axioms for Sets / h. Axiom of Replacement VII
Replacement: ∀x∈A ∃!y φ(x,y) → ∃Y ∀X∈A ∃y∈Y φ(x,y) [Kunen]
     Full Idea: Axiom of Replacement Scheme: ∀x ∈ A ∃!y φ(x,y) → ∃Y ∀X ∈ A ∃y ∈ Y φ(x,y). That is, any function from a set A will produce another set Y.
     From: Kenneth Kunen (Set Theory [1980], §1.6)
4. Formal Logic / F. Set Theory ST / 4. Axioms for Sets / i. Axiom of Foundation VIII
Foundation:∀x(∃y(y∈x) → ∃y(y∈x ∧ ¬∃z(z∈x ∧ z∈y))) [Kunen]
     Full Idea: Axiom of Foundation: ∀x (∃y(y ∈ x) → ∃y(y ∈ x ∧ ¬∃z(z ∈ x ∧ z ∈ y))). Aka the 'Axiom of Regularity'. Combined with Choice, it means there are no downward infinite chains.
     From: Kenneth Kunen (Set Theory [1980], §3.4)
4. Formal Logic / F. Set Theory ST / 4. Axioms for Sets / j. Axiom of Choice IX
Choice: ∀A ∃R (R well-orders A) [Kunen]
     Full Idea: Axiom of Choice: ∀A ∃R (R well-orders A). That is, for every set, there must exist another set which imposes a well-ordering on it. There are many equivalent versions. It is not needed in elementary parts of set theory.
     From: Kenneth Kunen (Set Theory [1980], §1.6)
4. Formal Logic / F. Set Theory ST / 4. Axioms for Sets / k. Axiom of Existence
Set Existence: ∃x (x = x) [Kunen]
     Full Idea: Axiom of Set Existence: ∃x (x = x). This says our universe is non-void. Under most developments of formal logic, this is derivable from the logical axioms and thus redundant, but we do so for emphasis.
     From: Kenneth Kunen (Set Theory [1980], §1.5)
4. Formal Logic / F. Set Theory ST / 4. Axioms for Sets / n. Axiom of Comprehension
Comprehension: ∃y ∀x (x ∈ y ↔ x ∈ z ∧ φ) [Kunen]
     Full Idea: Comprehension Scheme: for each formula φ without y free, the universal closure of this is an axiom: ∃y ∀x (x ∈ y ↔ x ∈ z ∧ φ). That is, there must be a set y if it can be defined by the formula φ.
     From: Kenneth Kunen (Set Theory [1980], §1.5)
     A reaction: Unrestricted comprehension leads to Russell's paradox, so restricting it in some way (e.g. by the Axiom of Specification) is essential.
4. Formal Logic / F. Set Theory ST / 4. Axioms for Sets / o. Axiom of Constructibility V = L
Constructibility: V = L (all sets are constructible) [Kunen]
     Full Idea: Axiom of Constructability: this is the statement V = L (i.e. ∀x ∃α(x ∈ L(α)). That is, the universe of well-founded von Neumann sets is the same as the universe of sets which are actually constructible. A possible axiom.
     From: Kenneth Kunen (Set Theory [1980], §6.3)
7. Existence / D. Theories of Reality / 10. Vagueness / b. Vagueness of reality
Objects such as a cloud or Mount Everest seem to have fuzzy boundaries in nature [Keefe/Smith]
     Full Idea: A common intuition is that a vague object has indeterminate or fuzzy spatio-temporal boundaries, such as a cloud. Mount Everest can only have arbitrary boundaries placed around it, so in nature it must have fuzzy boundaries.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §5)
     A reaction: We would have to respond by questioning whether Everest counts precisely as an 'object'. At the microscopic or subatomic level it seems that virtually everything has fuzzy boundaries. Maybe boundaries don't really exist.
7. Existence / D. Theories of Reality / 10. Vagueness / c. Vagueness as ignorance
If someone is borderline tall, no further information is likely to resolve the question [Keefe/Smith]
     Full Idea: If Tek is borderline tall, the unclarity does not seem to be epistemic, because no amount of further information about his exact height (or the heights of others) could help us decide whether he is tall.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §1)
     A reaction: One should add also that information about social conventions or conventions about the usage of the word 'tall' will not help either. It seems fairly obvious that God would not know whether Tek is tall, so the epistemic view is certainly counterintuitive.
The simplest approach, that vagueness is just ignorance, retains classical logic and semantics [Keefe/Smith]
     Full Idea: The simplest approach to vagueness is to retain classical logic and semantics. Borderline cases are either true or false, but we don't know which, and, despite appearances, vague predicates have well-defined extensions. Vagueness is ignorance.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §1)
     A reaction: It seems to me that you must have a rather unhealthy attachment to the logicians' view of the world to take this line. It is the passion of the stamp collector, to want everything in sets, with neatly labelled properties, and inference lines marked out.
The epistemic view of vagueness must explain why we don't know the predicate boundary [Keefe/Smith]
     Full Idea: A key question for the epistemic view of vagueness is: why are we ignorant of the facts about where the boundaries of vague predicates lie?
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §2)
     A reaction: Presumably there is a range of answers, from laziness, to inability to afford the instruments, to limitations on human perception. At the limit, with physical objects, how do we tell whether it is us or the object which is afflicted with vagueness?
7. Existence / D. Theories of Reality / 10. Vagueness / f. Supervaluation for vagueness
Supervaluationism keeps true-or-false where precision can be produced, but not otherwise [Keefe/Smith]
     Full Idea: The supervaluationist view of vagueness is that 'tall' comes out true or false on all the ways in which we can make 'tall' precise. There is a gap for borderline cases, but 'tall or not-tall' is still true wherever you draw a boundary.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §1)
     A reaction: [Kit Fine is the spokesperson for this; it preserves classical logic, but not semantics] This doesn't seem to solve the problem of vagueness, but it does (sort of) save the principle of excluded middle.
Vague statements lack truth value if attempts to make them precise fail [Keefe/Smith]
     Full Idea: The supervaluationist view of vagueness proposes that a sentence is true iff it is true on all precisifications, false iff false on all precisifications, and neither true nor false otherwise.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §3)
     A reaction: This seems to be just a footnote to the Russell/Unger view, that logic works if the proposition is precise, but otherwise it is either just the mess of ordinary life, or the predicate doesn't apply at all.
Some of the principles of classical logic still fail with supervaluationism [Keefe/Smith]
     Full Idea: Supervaluationist logic (now with a 'definite' operator D) fails to preserve certain classical principles about consequence and rules of inference. For example, reduction ad absurdum, contraposition, the deduction theorem and argument by cases.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §3)
     A reaction: The aim of supervaluationism was to try to preserve some classical logic, especially the law of excluded middle, in the face of problems of vagueness. More drastic views, like treating vagueness as irrelevant to logic, or the epistemic view, do better.
The semantics of supervaluation (e.g. disjunction and quantification) is not classical [Keefe/Smith]
     Full Idea: The semantics of supervaluational views is not classical. A disjunction can be true without either of its disjuncts being true, and an existential quantification can be true without any of its substitution instances being true.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §3)
     A reaction: There is a vaguely plausible story here (either red or orange, but not definitely one nor tother; there exists an x, but which x it is is undecidable), but I think I will vote for this all being very very wrong.
Supervaluation misunderstands vagueness, treating it as a failure to make things precise [Keefe/Smith]
     Full Idea: Why should we think vague language is explained away by how things would be if it were made precise? Supervaluationism misrepresents vague expressions, as vague only because we have not bothered to make them precise.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §3)
     A reaction: The theory still leaves a gap where vagueness is ineradicable, so the charge doesn't seem quite fair. Logicians always yearn for precision, but common speech enjoys wallowing in a sea of easy-going vagueness, which works fine.
7. Existence / D. Theories of Reality / 10. Vagueness / g. Degrees of vagueness
A third truth-value at borderlines might be 'indeterminate', or a value somewhere between 0 and 1 [Keefe/Smith]
     Full Idea: One approach to predications in borderline cases is to say that they have a third truth value - 'neutral', 'indeterminate' or 'indefinite', leading to a three-valued logic. Or a degree theory, such as fuzzy logic, with infinite values between 0 and 1.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §1)
     A reaction: This looks more like a strategy for computer programmers than for metaphysicians, as it doesn't seem to solve the difficulty of things to which no one can quite assign any value at all. Sometimes you can't be sure if an entity is vague.
People can't be placed in a precise order according to how 'nice' they are [Keefe/Smith]
     Full Idea: There is no complete ordering of people by niceness, and two people could be both fairly nice, nice to intermediate degrees, while there is no fact of the matter about who is the nicer.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §4)
     A reaction: This is a difficulty if you are trying to decide vague predicates by awarding them degrees of truth. Attempts to place a precise value on 'nice' seem to miss the point, even more than utilitarian attempts to score happiness.
If truth-values for vagueness range from 0 to 1, there must be someone who is 'completely tall' [Keefe/Smith]
     Full Idea: Many-valued theories still seem to have a sharp boundary between sentences taking truth-value 1 and those taking value less than 1. So there is a last man in our sorites series who counts as 'completely tall'.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §4)
     A reaction: Lovely. Completely nice, totally red, perfectly childlike, an utter mountain, one hundred per cent amused. The enterprise seems to have the same implausibility found in Bayesian approaches to assessing evidence.
How do we decide if my coat is red to degree 0.322 or 0.321? [Keefe/Smith]
     Full Idea: What could determine which is the correct function, settling that my coat is red to degree 0.322 rather than 0.321?
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §4)
     A reaction: It is not just the uncertainty of placing the coat on the scale. The two ends of the scale have all the indeterminacy of being red rather than orange (or, indeed, pink). You are struggling to find a spot on the ruler, when the ruler is placed vaguely.
8. Modes of Existence / A. Relations / 4. Formal Relations / b. Equivalence relation
An 'equivalence' relation is one which is reflexive, symmetric and transitive [Kunen]
     Full Idea: R is an equivalence relation on A iff R is reflexive, symmetric and transitive on A.
     From: Kenneth Kunen (The Foundations of Mathematics (2nd ed) [2012], I.7.1)
9. Objects / B. Unity of Objects / 3. Unity Problems / e. Vague objects
Vague predicates involve uncertain properties, uncertain objects, and paradoxes of gradual change [Keefe/Smith]
     Full Idea: Three interrelated features of vague predicates such as 'tall', 'red', 'heap', 'child' are that they have borderline cases (application is uncertain), they lack well-defined extensions (objects are uncertain), and they're susceptible to sorites paradoxes.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §1)
     A reaction: The issue will partly depend on what you think an object is: choose from bundles of properties, total denial, essential substance, or featureless substance with properties. The fungal infection of vagueness could creep in at any point, even the words.
Many vague predicates are multi-dimensional; 'big' involves height and volume; heaps include arrangement [Keefe/Smith]
     Full Idea: Many vague predicates are multi-dimensional. 'Big' of people depends on both height and volume; 'nice' does not even have clear dimensions; whether something is a 'heap' depends both the number of grains and their arrangement.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §1)
     A reaction: Anyone who was hoping for a nice tidy theory for this problem should abandon hope at this point. Huge numbers of philosophical problems can be simplified by asking 'what exactly do you mean here?' (e.g. tall or bulky?).
If there is a precise borderline area, that is not a case of vagueness [Keefe/Smith]
     Full Idea: If a predicate G has a sharply-bounded set of cases falling in between the positive and negative, this shows that merely having borderline cases is not sufficient for vagueness.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §1)
     A reaction: Thus you might have 'pass', 'fail' and 'take the test again'. But there seem to be two cases in the border area: will decide later, and decision seems impossible. And the sharp boundaries may be quite arbitrary.
14. Science / A. Basis of Science / 3. Experiment
The 'experimenter's regress' says success needs reliability, which is only tested by success [Reiss/Sprenger]
     Full Idea: The 'experimenter's regress' says that to know whether a result is correct, one needs to know whether the apparatus is reliable. But one doesn't know whether the apparatus is reliable unless one knows that it produces correct results ...and so on.
     From: Reiss,J/Spreger,J (Scientific Objectivity [2014], 2.3)
     A reaction: [H. Collins (1985), a sociologist] I take this to be a case of the triumphant discovery of a vicious circle which destroys all knowledge turning out to be a benign circle. We build up a coherent relationship between reliable results and good apparatus.
14. Science / C. Induction / 6. Bayes's Theorem
The Bayesian approach is explicitly subjective about probabilities [Reiss/Sprenger]
     Full Idea: The Bayesian approach is outspokenly subjective: probability is used for quantifying a scientist's subjective degree of belief in a particular hypothesis. ...It just provides sound rules for learning from experience.
     From: Reiss,J/Spreger,J (Scientific Objectivity [2014], 4.2)