Dictionary of Arguments


Philosophical and Scientific Issues in Dispute
 
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The author or concept searched is found in the following 2 entries.
Disputed term/author/ism Author
Entry
Reference
Probability Function Fraassen I 164
Probability function/Fraassen: is formally such thing as a mass. We can express it in the form of volume x density. - e.g. prblty changes in time in a manner which is characterized by a constant density.
"Flow" of possible states through the region X (in phase space)) is formally like the flow of an incompressible fluid. - ((s) The density does not change). - The distribution is then still even afterwards.) >Probability.

Fr I
B. van Fraassen
The Scientific Image Oxford 1980

Probability Function Lewis V 137
Probability function/Lewis: supposed to represent the belief systems of people. - These do not need to be realistic . Probabilities: are probability functions - the indicative conditional must have a fixed interpretation for different beliefs. - This makes it a probability conditional. >Conditional, >Probability conditional.
V 147
Probability function/Lewis: we can imagine it as distributing probabilities over the worlds. - Each world has a probability P(W) and the probabilities of worlds add up to 1. - We get to the probability of sentences by adding up the probabilities of worlds where the sentence is true. - All probability is concentrated in the A-worlds. >Possible world/Lewis, >Terminology/Lewis.

Lewis I
David K. Lewis
Die Identität von Körper und Geist Frankfurt 1989

Lewis I (a)
David K. Lewis
An Argument for the Identity Theory, in: Journal of Philosophy 63 (1966)
In
Die Identität von Körper und Geist, Frankfurt/M. 1989

Lewis I (b)
David K. Lewis
Psychophysical and Theoretical Identifications, in: Australasian Journal of Philosophy 50 (1972)
In
Die Identität von Körper und Geist, Frankfurt/M. 1989

Lewis I (c)
David K. Lewis
Mad Pain and Martian Pain, Readings in Philosophy of Psychology, Vol. 1, Ned Block (ed.) Harvard University Press, 1980
In
Die Identität von Körper und Geist, Frankfurt/M. 1989

Lewis II
David K. Lewis
"Languages and Language", in: K. Gunderson (Ed.), Minnesota Studies in the Philosophy of Science, Vol. VII, Language, Mind, and Knowledge, Minneapolis 1975, pp. 3-35
In
Handlung, Kommunikation, Bedeutung, Georg Meggle Frankfurt/M. 1979

Lewis IV
David K. Lewis
Philosophical Papers Bd I New York Oxford 1983

Lewis V
David K. Lewis
Philosophical Papers Bd II New York Oxford 1986

Lewis VI
David K. Lewis
Convention. A Philosophical Study, Cambridge/MA 1969
German Edition:
Konventionen Berlin 1975

LewisCl
Clarence Irving Lewis
Collected Papers of Clarence Irving Lewis Stanford 1970

LewisCl I
Clarence Irving Lewis
Mind and the World Order: Outline of a Theory of Knowledge (Dover Books on Western Philosophy) 1991


The author or concept searched is found in the following 5 controversies.
Disputed term/author/ism Author Vs Author
Entry
Reference
Carnap, R. Goodman Vs Carnap, R. II 67
GoodmanVsCarnap/Reduction Sentences: the whole thing is pretty absurd. In my opinion, philosophy has the task to explicate, not to describe science (and the everyday language). The explication shall refer to pre-systematic use of the expressions of consideration, but does not need to comply with the order. It s all about economy and standardization.
Schurz I 219
Grue/Bleen/Goodman/Schurz: logical form: (B: observes G*: grue) G*: ((Bxt0 > Gx) u (~Bxt0 > Rx)). Sa: Emerald. Sample: {a:1 ‹ i ‹ n} Then the assertions Sai u Bat0 u Gai and Sai u Bat0 u G*ai are equivalent b< definition. If we apply the inductive generalization conclusion both for "green" and for "grue", our sample results in the two universal hypotheses H: = "All emeralds are green" and H*: = "All emeralds are grue". Problem: H and H* imply for all emeralds not observed before t0 conflicting forecasts (green vs red). Schurz: the following relationship exists to subjective inductive exchangeability assumptions: for regular probability functions the exchangeability assumption cannot be valid at the same time for the predicate (Gx) and its pathological counterpart (G*). Question: according to which criteria should we decide which predicates we consider as exchangeable or inductively projectable? Many criteria were proposed and proved to be unsuitable. Carnap: (1947.146 1976, 211): Thesis: only qualitative predicates are inducible (projectable) "grue" is a Def "Positional" Predicate/Carnap, that is a predicate that refers to the time t0 in its definition. E.g. grue.
Def Qualitative Predicate/Carnap: has no definitional reference to individual constants.
GoodmanVsCarnap: (Goodman 1955/75, 105): Problem of language dependence (sic: dependence): through reciprocal re-definition it is possible to move from our own language (with "green" and "red") to a language which is equivalent in its expressiveness and in which "grue" and "bleen"(G * x * x R,) act as basic concepts (basic predicates):
Re-Definition/Language Dependence/Logical Form:
Language L (Gx, Rx primitive) language L* (G*x, R*x primitive)
Definitions in L Definitions in L*
G*x: ‹› ((Bxt0 > Gx) u (~Bxt0 › Rx)) Gx: ‹› ((Bxt0 › G*x) u (~Bxt0 › R*x))
R*x: ‹› ((Bxt0 › Rx) u (~Bxt0 › Gx)) Rx: ‹› ((Bxt0 > R*x) u (~Bxt0 › G*x)). Solution/Schurz: it is possible to distinguish between qualitative and positional predicates in terms of ostensive learnability independent of the language! I 220 GoodmanVsInduction/Schurz: this does not answer why induction should be based on qualitative and not on positional predicates. Induction consists in extending pattern that were so far observed as consistent into the future. To be able to formulate useful induction rules we need to know what remained constant!
And that depends on the qualitative features. Positional features are pseudo-features.
Important argument: the fact that individuals are "constantly" "grue" means that they change their color from green to red at t0 .
In this case, we have carried out "anti-induction" and not induction. That is the reason why we (with Carnap) have basic predicates for qualitative and not positional features for induction rules.

G IV
N. Goodman
Catherine Z. Elgin
Reconceptions in Philosophy and Other Arts and Sciences, Indianapolis 1988
German Edition:
Revisionen Frankfurt 1989

Goodman I
N. Goodman
Ways of Worldmaking, Indianapolis/Cambridge 1978
German Edition:
Weisen der Welterzeugung Frankfurt 1984

Goodman II
N. Goodman
Fact, Fiction and Forecast, New York 1982
German Edition:
Tatsache Fiktion Voraussage Frankfurt 1988

Goodman III
N. Goodman
Languages of Art. An Approach to a Theory of Symbols, Indianapolis 1976
German Edition:
Sprachen der Kunst Frankfurt 1997

Schu I
G. Schurz
Einführung in die Wissenschaftstheorie Darmstadt 2006
Field, H. Schiffer Vs Field, H. I 105
SchifferVsField: wrong is his suggestion: physical relations as an explanation for the reference relation would also cover relations to things of which they are not true. (E.g. >"Arthritis"/"shmarthritis", E.g. >Addition/Quaddition. - FieldVsPhysicalism). Conclusion: no functional relation, which operates without disquotation scheme will be appropriate for the "true-of" relation. ((s) Anyway not the relation, but the theory works, if at all with the disquotation scheme.).
I 109
Def Conceptual Role/c.r./Field: (Field 1977): the subjective conditional probability-function of an agent Two mental representations S1 and S2 have the same cr for one person, iff. their (the person’s) subjective conditional prblty-function is so that s for any mental representation, given the subjective probability of s1 s is the same as that of s2 where s. SchifferVsField: This is of little use, because not two people have the same conditional probability function. But Field is anyway pessimistic with respect to a precise concept of intersubjective sameness of mental content that goes beyond sameness of referential significance.

Schi I
St. Schiffer
Remnants of Meaning Cambridge 1987
Jackson, F. Lewis Vs Jackson, F. V 154/155
Robust/LewisVsJackson: There are two form of robustness: Def robust1: A is robust1 with regard to B, if P(A) and P(A I B) are close and both are high (like Jackson). (probability).
Def robust2: A is robust2 with regard to B, if P(A) is high and remains high, even when we learn that B. (Learning!)
E.g. A is robust1 with regard to B only, but not with regard to B and E together. Then A will not be robust2 with regard to B.
A: "I will not believe that Reagan works for the KGB!"
B: "Reagan works for the KGB".
E: Not A. (I believe that Reagan works for the KGB.)
((s) robust1 on B only: even if "...I will not believe this" But only if both probabilities are high!)
not robust2: (learning): When I learn that he works for the KGB, I need to believe it.
Lewis: If the KGB is so successful to have one of their people on the presidential seat, then they will also control the news so that we do not learn about this. So P(A) and P(A I BE) are equally high.
But naturally P(A I BE) = 0. (If I believe that Reagan works for the KGB, I will not believe that he does not work for them = 0).
Learning: What I learn is what I need to believe (in order to have been able to learn). And this contrary to my initial original belief that the KGB is going to deceive me.
So A is not robust2 with regard to B.
Example Richmond Thomason: a man accepts: "If my wife cheats on me, I won't believe it (because she is clever)".
But he doesn't mean that if he is made to believe the antecedens, he will believe the consequences.
((s) Conditional(s): the A can become more and more likely here without the speaker believing it, but if the probability function for the speaker gets higher, he/she will reject the whole conditional.
Robust/Conditional/Lewis: which of the two types of robustness affects the indicative conditional?
It depends on robustness2: it signals more information.
V 15
On the other hand, robustness1 is much easier to determine. Both are equivalent on the assumption that the learner conditionalizes.
R1 is a good guide for R2, which is really important. It is not surprising that we can signal R1, even if it clearly diverges from R2!
Example I can very well say: "If Reagan works for the KGB, I'll never believe it!".
Stalnaker I 269
Def Phenomenal Information/Terminology/Lewis/Stalnaker: is - beyond physical information - an irreducible different kind of information. The two are independent of each other. Stalnaker: it is the kind of information Jackson's color researcher Mary acquires.
It must be included in a non-centered description of the world.
Lewis/Stalnaker: had designed it for a possible response LewisVsJackson. But:
I 270
LewisVsPhenomenal Information/LewisVsJackson: enriching our description of the world would not in itself solve the problem of what it is that Mary does not know. Lewis: For example parapsychology: is what one could call the science of non-physical things. Suppose we learn as much about parapsychology as possible. Yet we would always not know "what it is like..."
Stalnaker: this is the same argument as Nagel's against the ontological view of self-localization. It is in vain to try to objectify a certain type of information, because the information "as it is..." will always be omitted.
Objectification/VsVs: could then answer that this special information is only accessible to the subject. (see above: like Frege).
Intentionality/Stalnaker: this requires access to intentionality, which explains how objective content can have this particular status.
Semantic diagnosis/Stalnaker: seems to me to dampen the temptation to objectify the content.
StalnakerVsObjectivation: (of subjective content)
1. takes on an extravagant metaphysics.
2. requires an explanation of the special relation we should still have additionally.

Lewis I
David K. Lewis
Die Identität von Körper und Geist Frankfurt 1989

Lewis I (a)
David K. Lewis
An Argument for the Identity Theory, in: Journal of Philosophy 63 (1966)
In
Die Identität von Körper und Geist, Frankfurt/M. 1989

Lewis I (b)
David K. Lewis
Psychophysical and Theoretical Identifications, in: Australasian Journal of Philosophy 50 (1972)
In
Die Identität von Körper und Geist, Frankfurt/M. 1989

Lewis I (c)
David K. Lewis
Mad Pain and Martian Pain, Readings in Philosophy of Psychology, Vol. 1, Ned Block (ed.) Harvard University Press, 1980
In
Die Identität von Körper und Geist, Frankfurt/M. 1989

Lewis II
David K. Lewis
"Languages and Language", in: K. Gunderson (Ed.), Minnesota Studies in the Philosophy of Science, Vol. VII, Language, Mind, and Knowledge, Minneapolis 1975, pp. 3-35
In
Handlung, Kommunikation, Bedeutung, Georg Meggle Frankfurt/M. 1979

Lewis IV
David K. Lewis
Philosophical Papers Bd I New York Oxford 1983

Lewis V
David K. Lewis
Philosophical Papers Bd II New York Oxford 1986

Lewis VI
David K. Lewis
Convention. A Philosophical Study, Cambridge/MA 1969
German Edition:
Konventionen Berlin 1975

LewisCl
Clarence Irving Lewis
Collected Papers of Clarence Irving Lewis Stanford 1970

LewisCl I
Clarence Irving Lewis
Mind and the World Order: Outline of a Theory of Knowledge (Dover Books on Western Philosophy) 1991

Stalnaker I
R. Stalnaker
Ways a World may be Oxford New York 2003
Popper, K. Schurz Vs Popper, K. I 115
Principal Principle/PP/Statistics/Schurz: the subjective probabilities must agree with them when the objective probabilities are known. Lewis: (1980): singular principal principle: subjectivist. Here "objective" singular propensities are simply postulated.
SchurzVsPropensity/SchurzVsPopper: it remains unclear which property a singular propensity should correspond to at all.
Solution/de Finetti: you can also accept the objective probability concept at the same time.
Conditionalization/Statistics/Schurz: on any experience date E(b1...bn) about other individuals b1,...bn it is important to derive two further versions of the principal principle:
1. Principal Principle for random samples used for the subjective justification of statistical likelihood intuition
2. The conditional principal principle, for the principle of narrowest reference class and the inductive statistical specialization conclusion is subject.
Principal Principle: w(Fa I p(Fx) = r u E(b1,...bn)) = r
Principal Principle for random samples: w(hn(Fx) = k/n I p(Fx) = r) = (nk) rk mal (1 r)n-k.
Conditional Principal Principle: w(Fa I Ga u p(Fx I Gx) = r u E(b1,…bn)) = r.
Principal Principle: is only useful for subjective a priori probabilities. I.e. belief degrees of a subject who has not yet had any experience.
Actual Belief Degree/Belief Degree: the principle does not apply generally for it: for example if the coin is already showing head (=Fa) the belief degree of it is of course = 1, while one knows that p(Fx) = ½.
Apriori probability function: here all background knowledge W must be explicitly written into the antecedens of a conditional probability statement w( - I W).
actual: = personalistic.
apriori probability: connection with updated probability function:
Strict Conditionalization/Schurz: w0 is the a priori probability or probability to t0 and w1 the current probability.
I 116
Wt is the knowledge acquired between t0 and t1. Then for any A applies:
Wt(A) = w0(A I Wt).
Narrowest reference class/n.r.c./Principle/Schurz: can be justified as follows: for a given event Fa, the individual can belong to a great many reference classes that assign very different probabilities to Fx. Then we got contradictory predictions. Question: but why should the appropriate reference class be the narrowest? Because one can prove that it maximizes the frequency value of true predictions.

Schu I
G. Schurz
Einführung in die Wissenschaftstheorie Darmstadt 2006
Salmon, W.C. Cartwright Vs Salmon, W.C. Cartwright I 26
Example Uranium/Decay/Probability/Cartwright: here it is not the statistical law (which Salmon quotes): P(clicks I uranium) < P(clicks) but rather the causal law: "uranium causes radioactivity". Then - as desired - the probability function for decay grows in every test situation. I.e. uranium amplifies the probability in both cases: when polonium is present and when it is absent. Salmon: sees the probability decrease because he considers a causally not homogeneous situation.
CartwrightVsSalmon, Probability: insisting on an increase in probability functions through all test situations not only gets all good cases, but also excludes bad explanations that Salmon must allow.
Schurz I 234
Probability/Explanation/W.Salmon/Ontology/Schurz: (Salmon 1971, 63, 1984): for example, if an unlikely event occurs, the explanation must contain the low probability value! And this is then the reason! For example in a Mendel crossing experiment the probability for red is 75 % and for white 25 %. Then the occurrence of white must be justified with the probability of 25 % (against 75 %)! Logical form: "p(white(x) I Ax) = 25 %, Ab// (0,25) White(b)". Although the antecedence here lowers the probability of the Explanadum event!
I 235
Salmon: therefore we can only demand from the antecedent that it is positively or negatively relevant. Hempel/Schurz: the late Hempel was convinced of this.
CartwrightVsSalmon, probability: it is counterintuitive to say that the event occurred because a factor was present that makes it unlikely.
Solution/Humphreys/Schurz: (Humphreys 1989,117) We refer to these as counter-causes. (Schurz pro). We then say that the event has occurred even though the antecedent has occurred.

Car I
N. Cartwright
How the laws of physics lie Oxford New York 1983

CartwrightR I
R. Cartwright
A Neglected Theory of Truth. Philosophical Essays, Cambridge/MA pp. 71-93
In
Theories of Truth, Paul Horwich Aldershot 1994

CartwrightR II
R. Cartwright
Ontology and the theory of meaning Chicago 1954

Schu I
G. Schurz
Einführung in die Wissenschaftstheorie Darmstadt 2006