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PoS Lectures 1 - 3

The lectures one till three
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Philosophy of Science (BT1107)

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Studiejaar: 2017/2018
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Lecture 1

Introduction of PoS: Ontology & Epistemology

Sumantra Ghoshal claims: Negative image of economic theory and agency theory (in particular) + the pretence of absolute knowledge in management (positivism and determinism) = the cause of economic failures at the turn of the century (frauds).

 Economic theory/agency theory: These assumptions are known to be not trully decision making is not truly rational, but are still the foundation for corporate governance.  The pretence: We make decision all the time. Going to the lecture is a choice. Very often we treat these choices as free choices, because it is your responsibility. The world makes assumptions that you are the one making your decisions, but is that really true? The world is causally determined.  Positivism: That knowledge and science is purely based on facts.

Animal behaviour We tend to explain animal behaviour causally by referring to instincts or biologically evolved natural dispositions. But Orca’s seem to be intelligent creatures in a similar sense that humans are. In explaining human behaviour, we often use intentional explanations, involving certain states of mind. We additionally hold strong philosophical intuitions about human intentions and behaviour: - Free will (metaphysics); - Reason (but what is reason?); - Moral responsibility (ethics).

On one hand we have determinism, and on the other conscious choice.

Should we explain human behaviour causally or intentionally? We tend to use causal explanation in natural science, such as physics or biology. We tend to use intentional explanation in social science, such as management.

Causality Causality is explaining outcome Y in terms of the necessary and/or sufficient conditions (X) for Y to take place. It has a strong connection with determinism: - The ontology that if we would know all applicable laws of nature as well as the initial conditions, we can perfectly predict what will happen in the future. - Determinism is sort of the ‘house ontology’ of natural science.

A counter fall understanding causation is currently the dominant view in social science: - An outcome Y, is caused by a cause, if and only if when X had occurred, Y would also have occurred AND, if X had not occurred, Y would also not have happened. - The laboratory experiment ‘operationalises’ this counter fall conception of causality in behaviour research.

Causal explanation in social science - Ontological questions: Are humans and social reality deterministic in the same way that we believe physical reality to be? o Individual level: free will, intentions, choice, individual responsibility; o Social level: Isn’t social humanly constructed in a way that physical reality is not?  Is reality real, or is it just my way of seeing reality? A theory of what reality is like, what the world is like. - Epistemology: Can we study social reality in the same way we study physical reality? o Can and should we explain human behaviour and social reality causally? o What is the role of other types of explanation (functional, intentional) in social science? o Can social science theories be based on observations alone?  What is knowledge? Do my notions taint my knowledge?

Bidirectional causality: economic development causes institutional development and the other way around.

Goshal: Is the reality that we study the same as physical reality? Why this is not the case: Take the Euro. That continues to exist if we accept it as a currency. But look back at the financial crisis, when Germany wanted to stop using the Euro.

Social ontology Do markets, organisations, money really exist in the same way that oxygen exists? Or do they exist only because we make them exist and subsequently take their existence for granted? Are concepts and theories in management about reality, or do they create reality instead? This is eventually the self- fulfilling prophecy (e. a bank run). The double hermeneutic: we create reality through our assumptions. Things exist because we allow them to exist, purposefully or not.

Social ontology matters! We say, “Samsung infringed Apple’s patents” and “Goldman Sachs deceived their clients”. But can organisations really act by themselves? Or can only humans act? We make such assumptions in everyday life all the time: - Legal personality (firms are entities in themselves); - Corporate criminal liability

In an important sense, social reality exists only in so far as we accept it to exist in everyday reality. Whether we do accept social reality is dependent on our understanding of it (the double hermeneutic).

How wrong assumptions became real The negative assumptions about mankind is that humans only care about themselves.

Executive compensation as a ‘corporate governance treatment’: - Separation of ownership and control in publicly listed firms; - Assumption: managers are extrinsically motivated by financial rewards - LTIPs will align interests of managers and shareholders.

The theory was mostly based on ideology, not on facts: - Managerial motivations are much more complex as a matter of fact; - There was no evidence of an actual pay  performance relationship; - Even worse: there was no actual performance  pay relationship

While the negative side effects were ignored, executive pay sky-rocketed and became a corporate governance problem rather than a treatment!

  • (Behavioural) assumptions; o Example: The agency problem, humans are self-serving and only care about their own welfare. We know that it is not true, because humans care as much about themselves as they do about each other, especially about their children. Another, we are not fully rational. We make assumptions to model behaviour. we do this to reduce complexity and make simplified models.
  • The double hermeneutic; o Assumptions we make about reality that we behave are true, and we start behaving as if they are true, thereby making them so.
  • Causal explanation; o If X did not happen, then Y would not be there. We operationalise this in the lab experiment. Most research is not experimental. Research in behavioural science is, but management science is not.
  • Intentional explanation; o It could in theory be possible that there is a causal explanation of why we are in this lecture. If we could plug in a chip in our brain, it would know what decisions we make, before we do.
  • Functional explanation. o We explain things from their consequences, and the functions they have. Why do we have a heart? Because a heart is necessary to sustain life. Very common in business administration, management and economics.

Lecture 2

The ideal of positive science

Logical positivism The facts determine which theories are true or not. Our ideas are based on knowledge and observation. Metaphysic theories are theories that go behind the appearances, and beyond what we can see.

Historical background Movement for positivism came to life in post-World War 1 Vienna. There was despair and disillusionment. World War 1 resulted from irrational (nationalistic) sentiments and dramatic miscalculations. Science could lead the way out of misery. Science could offer certainty where metaphysics and religion failed. It could also provide a rational social ordering instrument.

Philosophical background There were three grand theories of knowledge (from an epistemology): - Rationalism o All our knowledge comes from thinking, and that thinking is the only source of knowledge. Our observations are not fully reliable. E. Descartes. The biggest problem with rationalism, as an epistemologist, you can’t explain things (world specifically) purely from this. What you put in, the assumptions, ultimately, this is what you get out. Put garbage in, get garbage out. Science that tends to use this, is maths and economics (modelling). - Empiricism o Empiricism and positivism are often used interchangeable. All our knowledge is based on our experience. Problems with this: there are things we simple can’t observe, e. what does causality mean. We can’t see that A causes B. having things to say about this room, is data, not knowledge. Analysing data does lead to knowledge, but can also be manipulated. We have to add something to make the data, the observations, to turn them into knowledge. - Idealism o In order for observations to work, we have to order them. We use our ability to do this, or innate to understand reality, the knowledge about experience, rather than

experience itself. “idealism is the group of philosophies which assert that reality, or reality as we can know it, is fundamentally mental, mentally constructed, or otherwise immaterial. Epistemologically, idealism manifests as a scepticism about the possibility of knowing any mind-independent thing.” The observations itself are metaphysical.

Problem: how to structure observations without resorting to metaphysics: - Linguistic turn: the relation between us and what is out there, knowledge, is not that central. Logic can structure observations non-metaphysically. We don’t need metaphysics to structure our observations. We have language, a tool through which we can structure what we know about reality/knowledge. In language, we have logic. Luckily, language is not hidden, but accessible. Language by definition is shared between people, and not completely subjective.

DRAWING

2 building blocks in logical positivism Synthetic statements - The truth of a statement depends on matters of fact. - Method of verification is observation. o E. this circle has a 10-metre diameter.

Analytic statements: - The truth of a statement depends on the logical structure of a statement. - Method of verification is logical analysis. o E. this circle is round.

DRAWING

Key take-aways: - Starting point: o The relationship between language and reality. - Building blocks: o Synthetic and analytic statements. - Architecture: o Logical reduction to observations for all synthetic statements in system of knowledge. - Unity of science ideal.

Key take-aways: - Rationalism; - Empiricism; - Idealism; - Metaphysics; o Assumptions about what reality is like, that themselves are unobservable. E. cause and consequence. - The linguistic turn; o Used to be a relationship between subject and object, but now is the relationship between object and reality. How language can reflect the reality that we are studying. - Analytical statements; o Method of verification is analysis. You do not have to observe, but analyse a statement and based on the language rules, we can judge whether it is true or false. There is a difference between the conception of truth between analytic and synthetic. - Synthetic statements; - The requirements of logical reducibility; - The unity of science ideal. - Coherency of truth o There is a difference between the conception of truth between analytic and synthetic.

Formative concepts

These are all things that make democracy. Each add something, without which we could not speak of democracy. From the underlying cause to the symptoms, when looking at the arrows. Factor analysis is a method that if you measure many things, if there is an underlying cause that is causing everything.

A pragmatic concession Allow theoretical concepts in a system of knowledge if, and only if: 1. These concepts explain something in the facts that is not apparent from observation alone. a. Not just that XY but also explain why. E. copper is able to conduct electricity because of its free (un-localised) electrons. 2. The use of these concepts leads to the development of new knowledge (i. new hypotheses) to be tested.

 the acceptability of theoretical concepts depends on its explanatory properties. Concepts are theories by themselves, explaining the structure by the explanatory properties of the concept. Concepts are theories by themselves.

Deduction NB: New information cannot change the truth value of the conclusion anymore: i. the conclusion is given once the premises are given! Logical says that you cannot derive a false from only true statements. It can change the truth value of proposition 1, but not the conclusion. This is logically valid; hence we can use it in a system of analytical statements.

Induction NB: New information can change the truth of value of the conclusion! The problem with this is that this is not logically valid, and not the logical way of deriving things. Inferential statistics do not matter because you’re always going to have a large number of observations. The observation of 1 white raven, could already change the conclusion.

Adjustment of the L. model - Allow theoretical concepts in the system of knowledge. Hence a distinction should be made between theoretical and observational language in the system of knowledge.

  • Allow induction in the system of knowledge. Hence a distinction should be made between statements that are true, and statements that are merely likely to be true. The model of the empirical cycle Also known as the hypothetical-deductive method.

Critical rationalism Critical rationalism was created by Karl Raimund Popper. Popper’s criticism of standard view: - Criticism of logical positivism and the adjusted model of the hypothetical deductive method; - Problems in logical positivism and this model too fundamental for adjustments; - Proposal: a whole new model of science, and the model applies beyond science, e. into politics.

Problems with adjustments in standard view 1. Observation cannot be theory independent. It is always infected with theory and concepts and theory serve as searchlight theories. 2. Problem of induction cannot be adequately resolved.

Theory independent observation? We cannot observe anything if we have no idea what to look for. Observation means focussing. This is where the search light theory comes to play: - Concepts guide us in what to look for (e. inflation) and infect our reporting of what we see. - Theory embedded in observational instruments

The problem of induction Popper: adjustments in standard view are doomed to fail in regard to problem of induction: - Degree of confirmation will approach zero; - Striving for the highest truth-likeliness will lead to undesirable results; - Induction is wrong as a matter of principle!

Can we say something about unobserved cases X, or about the truth of general laws about X, based on observed cases of X? No!

Can we say something about the falsity of general laws about X, based on observed cases of X? Yes!

Degree of confirmation

Degreeof confirmation=

Numberof observedcasesof X

Allpossiblecasesof X

Popper’s critical rationalism 1. Rationalist element: o Develop theories that say as much as possible about reality (theory should have maximal empirical content). 2. Critical element: o Empirically test these theories as sharply as possible.

The Quine-Duhem thesis There are two dogma’s of empiricism according to Quine 1951. Assume that we define a raven as a(n): - Black; - Omnivore; - Bird of the genus corvus.

Hence the sentence “A raven is a black omnivorous bird of the genus corvus” is an analytical statement. But, what makes this statement an analytical truth? And: if we cannot really answer that question convincingly, why should we assume/believe that analytical statements cannot simply be falsified?

Quine There is no fundamental difference between analytical and synthetic sentences. When testing sentences, it is impossible to test individual sentences, as we can only test a whole system of sentences, e. a theory or a language. Every sentence within a system of knowledge – including analytical sentences – can be given up if to relieve a conflict between e theory and observations (experience). Which sentence you give up in case of a falsification is a pragmatic matter but one should never throw away your old shoes when you do not have new ones.

Duhem Every test of a hypothesis (H1) requires background assumptions (H2, H3, H4); e. searchlight theories embedded in measurement instruments. But if H1 is falsified, is it really H1 that is falsified or can it also be H2, H3, H4? Conclusion: we never test a single hypothesis but always a whole system of hypotheses that together constitute a theoretical conceptual framework.

Two kinds of meaning - Extension: The class of observable real-life phenomena to which a concept refers, e. the set of all existing ravens. - Intension: The conjunction of general attributes that define a concept (the conjuncts are each necessary and jointly sufficient), e. raven = a (1) black, (2) omnivorous, (3) bird of the genus corvus.

The conjunction A ∩ B ∩ C

Conflict between theory and observation 1. Raven = a black, omnivorous bird of the genus corvus; 2. X is a raven; 3. Hence, X is black.

Yet we observe: Raven X is white, making C untrue.

The conflict between theory and observation can be solved in two ways: - Proposition 1 (the definition) is false; - Proposition 2 (the observation) is an error, e. we were not observing correctly; X is not a raven but a gull.

What solution we choose to resolve the conflict between theory and observation is dependent on pragmatic consideration rather than principled ones.

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PoS Lectures 1 - 3

Vak: Philosophy of Science (BT1107)

52 Documenten
Studenten deelden 52 documenten in dit vak

Universiteit: Erasmus Universiteit Rotterdam

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Lecture 1
Introduction of PoS: Ontology & Epistemology
Sumantra Ghoshal claims:
Negative image of economic theory and agency theory (in particular) + the pretence of absolute
knowledge in management (positivism and determinism) = the cause of economic failures at the turn
of the century (frauds).
Economic theory/agency theory: These assumptions are known to be not trully decision
making is not truly rational, but are still the foundation for corporate governance.
The pretence: We make decision all the time. Going to the lecture is a choice. Very often we
treat these choices as free choices, because it is your responsibility. The world makes
assumptions that you are the one making your decisions, but is that really true? The world is
causally determined.
Positivism: That knowledge and science is purely based on facts.
Animal behaviour
We tend to explain animal behaviour causally by referring to instincts or biologically evolved natural
dispositions. But Orca’s seem to be intelligent creatures in a similar sense that humans are. In
explaining human behaviour, we often use intentional explanations, involving certain states of mind.
We additionally hold strong philosophical intuitions about human intentions and behaviour:
- Free will (metaphysics);
- Reason (but what is reason?);
- Moral responsibility (ethics).
On one hand we have determinism, and on the other conscious choice.
Should we explain human behaviour causally or intentionally? We tend to use causal explanation in
natural science, such as physics or biology. We tend to use intentional explanation in social science,
such as management.
Causality
Causality is explaining outcome Y in terms of the necessary and/or sufficient conditions (X) for Y to
take place. It has a strong connection with determinism:
- The ontology that if we would know all applicable laws of nature as well as the initial
conditions, we can perfectly predict what will happen in the future.
- Determinism is sort of the ‘house ontology’ of natural science.
A counter fall understanding causation is currently the dominant view in social science:
- An outcome Y, is caused by a cause, if and only if when X had occurred, Y would also have
occurred AND, if X had not occurred, Y would also not have happened.
- The laboratory experiment ‘operationalises’ this counter fall conception of causality in
behaviour research.

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