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Lecture:Philosophy of Science (Schurz) Ss 2015 Wed 10.30-12 24.91/U1.61

Part I: General introduction and philosophical foundations

1) 04-15 Tasks and aims of Philosophy of Science. The method of rational reconstruction

2) 04-22 Common epistemological assumptions and methodological features of the sciences

3) 04-29 Classification of scientific disciplines and the demarcation problem: The requirement of value neutrality

4) 05-06 Scientific inference: Deduction, induction and abduction

Part II: Logical foundations

5) 05-13 Kinds of concepts

6) 05-20 Kinds of sentences

7) 05-27 Degrees of generality. Logical relations between sentences

Part III: Law hypotheses and their empirical testing

8) 06-03Testingfor Truth and Relevance 1: the deterministic case

9) 06-10 Testingfor Truth and Relevance 2: the statistical case

10) 06-17 Correlation and causality

Part IV: Scientific theories

11) 06-24Observation concepts, empirical disposition concepts and theoretical concepts

12) 07-01 Structure and methodological features of scientific theories

Example 1: Newtonian physics

13) 07-08 Example 2: Piaget's cognitive psychology. Theory evaluation and theory progress

14) 07-15 Exam

Book to the lecture: Gerhard Schurz: Philosophy of Science: A Unified Approach, Routledge,New York 2013.

Furtherliterature (in red: recommended):

Bird, A. (1998): Philosophy of Science, McGill-Queen's University Press, MontrealKingston.

Bunge, M.: Scientific Research, Springer, Berlin 1967.

Carnap, R.: Philosophical Foundations of Physics, Basic Books, New York 1966.

Curd, M., and Cover, J.A. (1998, ed.): Philosophy of Science, Norton, New York.

Feyerabend, P.: Against Method, New Left Books 1975.

Godfrey-Smith. P. (2003): Theory and Reality: An Introduction to the Philosophy of Science, University of Chicago Press, Chicago.

Hempel, C. G.:Philosophy of Natural Science, Englewood Cliffs, Prentice Hall 1966.

Kuhn, T.: The Structure of Scientific Revolutions, 2nd ed., Univ. of Chicago Press 1975 (orig. 1962).

Ladyman, J. (2002): Understanding Science, Routledge, London.

Lakatos, I., Musgrave, A.:Criticism and the Growth of Knowledge, CambridgeUniversity Press 1970.

Losee, J. (2001):A Historical Introduction to the Philosophy of Science, OxfordUniv. Press, Oxford (Orig. 1972).

Popper, K.: The Logic of Scientific Discovery, Basic Books, New York 1959.

Psillos, S. (1999): Scientific Realism. How Science Tracks Truth, Routledge, London and New York.

Reichenbach, H.: The Rise of Scientific Philosophy, Univ. of California Press, Berkeley and Los Angeles 1951.

Van Fraassen, B.: The Scientific Image, Clarendon Press, Oxford 1980.

Questions of the General Philosophy of Science

General versus special characteristics of the sciences  including the natural sciences, social sciences and the humanities.

the objects

What arethe methods of the sciences ?

the goals and limitations

a scientific language

correct scientific argument

What is a scientific observation, fact or measurement?

a scientific law, a theory?

a prediction, explanation, causal relation ?

How are laws or theories empirically tested?

What are criteria for theory progress in science

What is objectivity and truth ? Philosophy of science epistemology

Values in science versus value-neutrality?Philosophy of science (meta-)ethics

Applications internal to sciences:

 Methodological advice and decision support on controversial questions in sciences

 Interdiscplinary relations and transdisciplinary discoveries

 Pioneer function for new sciences

Applications external to sciences:

Demarcation problem (example: controversy surroundingcreationism)

Critical function: critique of political or economical abuse of the sciences

(example: systematic biases in pharmaceutical research)

The method of the philosophy of science

The normative view (earlier): Karl Popper, Vienna circle (logical empiricism)

The descriptive view: Thomas Kuhn ('historical turn'), W. Stegmüller, L. Laudan R. Giere ()

Argument of the normativists: Context of discovery (genesis)

versus

context of justification ( confirmation)

The method of rational reconstruction (Lakatos1971, Stegmueller1979):

NORMATIVE CORRECTIVE

Supreme epistemic goal (Minimal) epistemological model

(Revision?) (Justification) (Revision?)

RATIONAL RECONSTRUCTION

Philosophy of Science develops models of:

Observation, experiment, law, theory, confirmation, disconfirmation

falsification, explanation, causality, theory progress ....

(empirical support) (application)

Real (factual) sciences Real sciences vs. pseudo-sciences

positive and negative paradigm cases Controversial cases

DESKRIPTIVE CORRECTIVEUnsolved problems

Supreme Goal: (G) Finding true and content-rich statements

relating to the given domain of investigation

 tension between probability of truth and richness of content

Minimal epistemological modell  five assumptions:

(E1) Minimal realism (correspondence theory of truth)

(E2) Fallibilism (critical attitude)

(E3) Objectivity & Intersubjectivity (criterion)

(E4) Minimal empiricism (empirical testability)

(E5) Logic in the broad sence (concepts, statements, arguments)

Minimal methodology  four methodological features:

(M1) Search of general and content-rich laws and theories

(M2)Search of actual observation statements

(M3) Attempt to explain the actual observation statements

and to predict potential observation statements,

with help of the laws or theories conjectured in (M1)

(M4) Attempt to test laws and theories by comparing the predicted (potential) observation statements with the

actual observation statements.

Agreement: Confirmation

Disagreement: Falsification or Disconfirmation

Three levels:

Scientific theories

Prediction explanation Confirmation disconfirmation

Empirical laws

Prediction explanationConfirmation disconfirmation

(Actual) observation statements

Classification of scientific disciplines, according to their domain of objects:

SCIENCES

1) of nature: physics, chemistry, biology, geology, medicine (astronomy, cosmology, geography, paleontology, history of biological evolution)

2)of technology:mechanical and electrical engineering …, also: computer science

3) of human beings: psychology (also: education, medicine, cognitive science)

4) of (human) society: sociology, economics, political science (also: anthropology, ethnology, geography)

5) of (human) history: history (also: anthropology, ethnology)

6) ofcultural (mental, social) artifacts:legal sciences, linguistics, literary science, sciences of fine arts and music,media studies (also: education, religious studies)

7) of formal structures (formal sciences): mathematics (logic, statistics, theoretical computer science, system theory…), formal methodology and philosophy of science

8) of the general foundations of human ideas: philosophy (epistemology, philosophy of science and theoretical philosophy; ethics, aesthetics and practical philosophy)

9) of God: theology (also: religious studies)

Natural sciences: only 1?, +2?, +7? +3?

Humanities: 5,6, 8 Why not 7? Or 3?

Human and social sciences: 3, 4 (5?, 6?) [Cultural sciences]

Factual sciences (as opposed to structural sciences): 1, 2, 3, 4, 5, 6 8?, 9??

Exceptional case of formal sciences 7: G; E1-E3, E5 (not E4); M1 (not M2-M4)

Demarcation:"Science" comprises all empirical sciences (satisfying G, E1-E5, M1-M4, plus their associated formal and methodological auxiliary sciences (7).

Limitations of science:

 where evaluative statements enter the discipline ( 6, 8, 9 )

 where assumptions of faith (religios creed) enter the discipline (9)

Example: Value judgement in jurisprudence (the science of legal judgment).

(Is a billboard advertising underwear still in accord with "common decency" or is it already a legal offense?)

Eike von Savigny et al. (1976)E. Hilgendorf and L. Kuhlen (eds., 2000)

Max Weber (1864-1920): Postulate of value-freedom

 because: Values are not properties inherent to objects themselves, butbased on subjective interpretations by us humans.Ultimately, the decision for or against certain values is a question of personal freedom.

However, the scientist qua scientist

(1.) can study the factual presence of value and norm systems,

(2.) can discover logical relationships among value or norm sentences (test them for inconsistencies), and

(3.) ( most importantly for practical sciences): can infer derived norms from given fundamental norms and descriptive knowledge, by means of the so-called

Means-end inference:

Descriptive means-end hypothesis: M is in the given circumstances C a necessary

 or alternatively an optimal  means for the realization of end E.

Thus:Given (fundamental norm:) end E is to be realized,

then (derived norm:) means M should also be realized.

The requirement of value-neutrality (VN) in sciences:

EVexternal values (all values except those in IV)

IVinternal values (supreme goal (G) and all values following from (G) by means-end inferences)

CDcontext of discovery

CJcontext of justification

CAcontext of application

EV & IVonly IV EV & IV

CD CJ CA

(VN): A specific realm of scientific activity, namely their context of justification, should be free from fundamental science-external value assumptions.

( A normative recommendation. Not a generally followed practice)

The selection of the investigated objects and parameters in (CD) is not epistemologically neutral, but places limits on the results of the scientific investigation.

Therefore the selection in (CD) must be accessibleto subsequent correction by results in (CJ) (even when this goes against the external goals of the research project).

Selection of relevant variables

Example: causal theories of psychological depression

•Hippocrates: surplus of black bile

•Middle Ages: devil and demons; punishment for laziness

•Astrology: star constellation

•Freud: child development, lack of satisfaction in oral phase

•Beck: cognitive defects

•Seligman: uncontrolled fear

•Genetics: genetic dispositions

•Neurophysiology: low level of neurotransmitters

Further classifications of disciplines:

Classification of factual sciences:

Speculation

Empirical sciences

Experimental sciences

Dissecting sciences

Graduated division of scientific methodologies by increasing degree () of logical-mathematical and quantitative precision

logical-mathematical language natural language

"quantitative" "qualitative"

Logic Hermeneutics

Statistics and measurement theory Content analysis

Technology Field research

What is the characteristics of "(natural) science":

empirical? experimental? dissecting?quantitative?

+ yes- no n naïve ? between + and - ?+ tends towards + ?- tends towards -

PositionVNA1A2A3A4A5M1M2M3M4

Pre-modern History

Plato-n+-+?-+---

Aristotle?-n+-++?-+-+?-

Alexandria+n+-++n++++n+

MA ≤ 12th century-n+-+?-+-+-

Late scholasticism ?++?++?+n++++n+

Modern Times

Empiricism

Bacon, Locke?+n+-+-n++++n+

Hume+-++-+++++

Mill?++-++n+++++

Rationalism

Descartes, Leibniz?-+-++-+-+-

Kant-+-++?+++?

Contemporary Phil of Sci

Logical Empiricism+?+++n+++++

Post-Positivism++++++++++

Pragmati(ci)sm?-++++++++

Contemporary criticisms:

Relativism

+/- moderate/radical?+/-+---+?+-

Constructivism

+/- moderate/radical?+/-?+/-+/-+/?++/-++/-

Hermeneutics?-?+ ++-?+-+-?

Critical theory--+---?+?++?+

The inductive –The general (laws and theories)

deductive schema: inductive ascent deductive descent

(Aristotle)

The particular (observations)

Induction in the broad sense: Induction (i.n.s.)+ abduction

Three kinds of scientific inference and argumentation:

Deduction- certain: Logic in the narrow sense

All As are Bs, this is an A / therefore: this is a B

(Other kinds of ded. inference: fromgeneral togeneral, fromparticular toparticular)

Induction- uncertain:

Inductive generalization:

AllAs observed so far were Bs // therefore (probably): allAs are Bs

[Statistical version: r% of observed As were Bs // therefore: r(% of As are Bs]

Inductive prediction:

AllAs observed so far were Bs // therefore: the next A will be a B

Abduction - very uncertain: Inference to the best explanation, or inference to an unobserved cause (theoretical concept)

This is an A. Can be explained (in given background knowledge) by the

assumptionthat this is a B //(Conjecture:) this is a B

Controversial: is abduction a scientifically legitimate form of inference?

Popper: No: abduction  discovery of hypotheses by trial and error

 But oh! Popper and his students even doubt the scientific legitimacy of induction

Three Kinds of Induction:

1. Methodological induction

Induction as a method of "extracting"laws and theories from observations

Example:AllAs observed so far were Bs  thereforeallAs are Bs

Major criticism of Popper:

Confusion of context of discovery and context of justification

Theories are not  or better: not only discovered by induction

2. Logical Induction (Carnap, Reichenbach, Bayesianismus):

Induction as a methodof justification: determining the conditional probabilityof scientific hypotheses H given the observational data O:

Probability(H / O) = so-and-so (e.g., 0.9)

Major criticism of Popper: The space of all possible alternative theories is unlimited and cannot be probabilistically measured.

3. Epistemic Induction (or meta-induction):

Induction as a merely comparative evaluation of the probability of scientific

hypotheses (laws or theories):

Theory T1 has been empiricallyWe believe that T1will be empirically

more successful than theory T2 more succesful than T2in the future

current state of observational knowledge

the degree of confirmation of a

theory is alwaysdoubly relative: current state of alternative theories.

Abduction to theories - example:

Planets move around the sun in elliptic orbits.

This can be explained by Newton's force laws (2nd law & gravitational law & cp).

// Abductive conjecture: Newtons' force laws are approximately true

Interaction of epistemic induction and abduction

(1) Evidence: Tk is amongthe alternative theories T1,,Tnso far the empirically most successful.

epistemic inductive inference

(2) Instrumentalist conclusion: Tk is among T1,,Tn the most empirically adequate (therefore also in future the most empirically successful)

abductive inference to the best theory

(3) Realistic conclusion: Tk is among T1,,Tn the closest to the truth.

 Empiricist instrumentalismversus realismin the philosophy of science

Kindsof concepts --- Classifications:

According to the logical type: (shorted presentation)

Singular concepts or terms(designate a single individual,

spatiotemporal location or situation)

Non-logical(individual constants: a, b, …)

concepts

General concepts

predicates one-place:express properties

or kinds (F, G, …)

n-place:express (n-ary)relations (R, …)

function symbols: expressfunctions (f, g, …)

LogicalTruthfunctional sentence operators not (), and (),

concepts inclusive or (), if-then (),  (prop. logic)

Quantifiers "for all" (), "exists" () (pred.logic) Intensional sentence operators necessary (), possible () probable (modal logic)

Variables (for individuals x, y,…; forpredicates ,  ,…)

Mathematical concepts (set theory), +, (arithmetics), …

According to the content type:

(logical concepts)observation concepts empirical

concepts

descriptive concepts empirical disposition concepts

(non-logicaltheoretical concepts

concepts)

prescriptivenorm concepts

concepts

value concepts

criterion for observability: ostensive learnability

observable in the narrow sense versus empirically measurable in the wide sense

According to the gradation (scale) type:

classificatory concepts

nominal (categorial) scales

qualitative concepts

comparative concepts

ordinal (ranking) scales

interval (difference) scales

quantitative concepts

ratio scales

Kindsof Sentences --- Classifications:

According to the content type:

logically determined

analytic

determined by definition

observation sentences ()

empirical general emp. sentences (...)

descriptive

synthetic theoretical purely theoretical

mixed-theoretical

normative

purely prescriptive

evaluative

mixed-prescriptive

(Simplified) definitions:

Observation sentence:a singular sentence (*), which contains (apart from logical concepts) only observation concepts. Example: "this raven is black".

(*: or a localized-quantified sentence: e.g., "all apples in this basket are red")

Empirical sentence:a (possibly quantified) sentence, which contains (apart from logical concepts)only empirical concepts. Example: all raven are black.

Theoretical sentence: a sentence that contains theoretical concepts (besides logical concepts and possibly empirical concepts). Example: "atoms consist of protons, neutrons and electrons", or "in the center of our galaxy there is a black hole".

(T-theoretical concept, T-theoretical sentence)

A sentence is purely descriptive iff it

(it either contains no prescriptive concept, or if)

every prescriptive concept occurring in it lies in the scope of a subjective

attitude operator

A sentence is purely prescriptive iff all of its descriptive components (subsentence or subformulas) lie within the scope of a prescriptive operator.

(In other words, iff all of its elementary subsentences/subformulas are elementary prescriptive sentences.)

A sentence is mixed otherwise(it has descriptive and prescriptive elementary subsentences/subformulas).

Examples:

Peter believes that stealing is bad.

Stealing is bad.

Stealing is allowed for a person, if this person is suffering from hunger.

Peter believes that stealing is bad, although he is a thief himself.

If stealing is permitted, then there exists no right to private property.

Peter's car has good breaks.

Peter has a good character.

A sentence is logically true iff every sentenceof the same logical form is true.

 in other words:iff its truth depends only on its syntactic structure and on the meaning of its logical concepts.

Logical form of a sentence:

Replace all nonlogical symbols by variables (dummy letters).

Example of a logically true sentence:

If all men are mortal, then there exists no man who is immortal.

Logical form: If all F are G, then there exists no F which is not a G

Formalization:x(FxGx) x(FxGx)

Example of a synthetically true sentence:

All men are mortal. (All F are G)

An argument (inference) is logically valid iff for every argument which has the same logical form the following holds: if all premises are true, theconclusion is true.

Example:Premise 1: All humans are mortal.

Premise 2: You are a human.

Conclusion: Therefore your are mortal.

Logical Form:All F are GFormalization:x(Fx Gx)

This a is an F Fa

Therefore this a is a G Ga

Example of an invalid argument:

All humans are mortal.All F are G

This living being is mortalThis a is a G

Therefore this living being is human.Therefore this a is an F

A sentence is definitorially(or: extralogically-analytically) true iff its truth is determined by certain conventions of meaning for its non-logical concepts (that are entrenchend in the underlying language or linguistic community)

Example: All bachelors are unmarried(Logical form: All F are G)

The length of the standard measure in Paris is one meter

Example of synthetical sentences:

All polar bears are white (Same logical form)

The length of this rod is one meter."

(Definiendum) (Definiens)

Explicit definitions:x: x is a bachelor defx is a hitherto unmarried man

Meaning postulates: If something is red, then it has a color.

Derived definitorially true sentences: If somebody is a bachelor, then he is male.

Requirements on definitions:

They must not be circular.

They must neither have empirical content, nor create new empirical content in combination with the given system S of accepted background beliefs beliefs.

Hence: No concept may be defined in two different ways.

Example: 1 Meter = the length of the platin-iridium-bar in Paris. (1)

1 Meter = the length of a pendulum at sea level with (2)

an oscillation frequency of one second.

(1) + (2) imply the following synthetical (empirical) consequence:

The length of the platin-iridium-bar in Paris= the length of a pendulum at sea level withan oscillation frequency of one second.

Classification of sentences

according to theirgenerality (logicalstrength):

Strict (or deterministic) generalizations

Purely universal sentences

e.g.: For all x: if x is A, then x is C x(AxCx))

'A' for 'antecedent', 'C' for 'consequent'

(spatiotemporally) unrestricted (spatiotemporally) restricted

Mixed-quantified generalizations; e.g. universal-existential (etc.).

General sentences

Non-strict generalizations

Statistical generalizations

e.g.: q % of all As are Cs p(C|A) = r (with: 0r1; q = 100r)

(spatiotemporally) unrestricted (spatiotemporally) restricted

Normic and ceteris paribus generalizations

e.g.: As are normally Cs and: C.P. As are Cs

Singular sentences e.g. This is an A, and it is (or is not) a C. Aa(Ca

Existential sentences e.g. There exists an A that is (or is not) a C. x(Ax(Cx)

(Mixed sentences)

Interlude: Two kinds of probability:

•1. Statistical (objective) probability:Always refers to classes, never to individual cases. "80% of all Italians are brown-eyed"

•2. Epistemic (subjective)probability:Rational degree of belief. Refers to individual cases. "With high probability Vicenco (from Italy) is brown-eyed"

Principle of narrowest reference class (Hans Reichenbach)

Important logical relations

Notation: "X  Y" stands for "Y follows logically from X",

and "X  Y" for "X and Y are logically equivalent".

(1) Universal sentence  singular sentence

All As are Cs  if a is A, then a is C

(2) Universal sentence & singular sentence singular sentence