Philosophy of Science Concepts

Natural Science

Physics, biology, chemistry, astronomy. Natural sciences focuses on universals and regularities, suggesting that the physical universe is uniform and simple. They zoom out from individual phenomena to the universal. Standard techniques of theorizing include mathematization, idealization, and abstraction. Due to this, it is able to yield knowledge in concise and powerful forms. Eg. the laws of nature in mathematical equations, eg law of gravity. Laws are taken as paradigmatic forms of knowledge as they. are taken to represent the highest grade of scientific knowledge. Further examples include the “scientific revolution”, “modern natural sciences (developed from China, India and Islamic sources)”, and “ancient intellectual endeavors (astronomy in Mesopotamia).

What does Multidisciplinary refer to?

The integration of knowledge and methods from multiple academic disciplines to address complex societal problems. It entails collaboration among different fields, diverse perspectives, and greater problem solving capacity. This approach is relevant to the climate crisis, migration, and conflict resolution. An example includes, the humanities field (senses of history, belonging, and recognition).

Human Science

History, art history, linguistics, philosophy, etc. Human science focusses more on ways of doing (how to) than knowing, which developed into ways of knowing during renaissance humanism in the 16 century. It focuses on historical human actors, thus people in history who have done things, who have created acts, texts, artworks. Human sciences zoom into historical particularity, (contrast to NS that zooms out into universal regularities). Events are unique and unrepeated and knowledge is intimate knowledge of particularities. No use for scientific laws. Main output of HS are interpretations (acts, texts, art) and are often embedded in theoretical frameworks. HS also attempts to reconstruct the historical actors world of experiences and meaning (hermeneutics).

Social science

Sociology, political science, economics, psychology, etc. Originated in the 19th century French and German debates on how to study societies. Social sciences feel the pull of both natural sciences and human sciences. Eg. Economics is a largely nomothetic discipline and is predominantly mathematical and Political Theory is a largely idiographic discipline that produces interpretations. Psychology can be both.

Nomothetic Approach

Proposed by Wilhelm Windelband as a response to how we can conceptualize the differences between NS, HS, and SS . This approach identifies regularities in the world, formulating generalizations and laws to describe these regularities. Thus, deriving explanations of observed outcomes from these generalizations and laws. This approach is typical of natural sciences. There can also be laws in social and human sciences.

Strengths: identifies similarities and structures that underlie diverse cases and yields general and economic knowledge.

Weakness: erases the specificity of outcomes and can be reductive, mechanistic, and positivistic.

Examples of nomothetic approach being broad (laws in every science): basic color terms, (rules n linguistics) as languages acquire color terms in similar orders.

Idiographic Approach

Proposed by Wilhelm Windelband as a response to how we can conceptualize the differences between NS, HS, and SS . This approach understands the meaning of contingent, unique, and subjective outcomes. Typical of human sciences. Essentially, the idiographic approach focuses on understanding specific individual cases in depth.

Strengths: reveal differences between apparently similar cases and yields detailed and context sensitive knowledge.

Weakness: Be blind to the general factors that constrain outcomes.

Induction

A technique for detecting regularities and formulating empirical laws. It is AMPLIATIVE unlike deduction, and an inductive generalization may be disconfirmed. Inductivist strategy works as follows: the observer notes any initial indication of regularity in a few cases: x1=A and B and x2= A and B so you can assume that all As = Bs. This is inductive generalization. (all swans are white assumption). Induction goes from particular to general.

Deduction

Goes from general to particular.

What is David Humes problem of Induction?

We cannot logically justify induction, or the idea that past patterns will continue in the future. If we try to justify induction using past successes then we are using induction again which is a circular reasoning then. If we try to use deduction then it is too limited to prove theories of the future. So, induction should simply be seen as a psychological tendency of the human mind.

What are responses to Humes thinking?

Poppwer → agrees and therefore we should cancel induction completely.

Reichenbach and Braithwaite → proposes vindications of induction like the pragmatic warrant; we do not know if the world contains any universal regularities, so since we cant know If the world does or not then induction is as good as any other theory to test these regularities.

3 forms of knowledge

1. Knowledge by acquaintance (“I know The Hague”)

2. Know-how → Practical knowledge or skill (“I know how to ride a bike”)

3. Know-that → Propositional knowledge (I know that P, where P is a proposition)

Propositional knowledge

The highest form of knowledge as it is the knowledge of facts.

JTB Account of Knowledge

Justified True Belief account says that propositional knowledge is a justified true belief. This idea was first proposed by Plato. Analyses the statement : “A knows that P” (A is a person and P is a proposition). However, A knows that P if and only if: P is true, A believes that P, and A is justified in believing that P. If these conditions hold, then A knows that P, if not, then it is not a case of knowledge. Essentially, the JTB account unpacks the concept of “knowledge”, showing how it related to the concepts of: truth, belief, and justification.

JTB applied to an example:

Jo (A) knows that it is raining (P) if and only if:

1. It is raining

2. Jo believes it is raining

3. Jo is justified in believing it is raining

Correspondence theory of truth

A proposition is true if and only if there is a fact corresponding to it. Facts make our positions true or false. Eg. “Snow is white” is true if and only if snow is white. Russel advocated this as the most influential account of truth.

Facts

A state of affairs that makes a proposition true according to the correspondence theory. The fact that the snow is actually white makes the proposition that “snow is white” true. Facts are truth-makers whereas positions are truth-bearers. Facts are not T/F they are/are not. Facts do not “change in time” eg. France in 1680 is a monarchy.

What is the Gettier problem a response to?

It reveled a flaw in the JTB account lets through some cases that we intuitively reject as knowledge, therefore it was discussed whether it should be JTB +. Alternative conceptions of truth and fact are available and examples are: Coherences theory of truth and Constructivist accounts of facts.

What does it take for an account to have the status of an explanation?

It needs to be true, otherwise it is a pseudo-explanation. Example, “lightening occurs because zeus is angry”, this does to explain lighting because it is simply not true.

Explanandum

What is being explained

Explanans

What does the exlaining

What are Hempels 2 models of explanation?

1. Deductive-nomological model (DN) model

2. Inductive-statistical (IS) model (extension of the DN model)

These two models offer a view of which formal requirements an explanation must satisfy.

Deductive-nomological model (DN)

An explanation is a valid deductive argument (D) from true premises, that includes at least one scientific law (N) and descriptions of some particular facts to a conclusion that states the explanandum. A flaw of the DN model: that it is too permissive as through relying on laws, it lacks the resources to distinguish causes and effects. And the DN model as explanation accepts some accounts that cite irrelevant factors (Eg. hexed salt)

Inductive-statistical model

Extension of DN model to probabilistic situations. In this model, an explanation is an argument that established that the explanandum has high probability, we call this inductive because it uses probable, not certain, reasoning. For example, explanandum: death of plant B, why did it die?, any plant sprayed with acid has the probability of dying and plant B way sprayed with that therefore it died. COUNTER: some scientific explanations do not make the explanandum highly likely, showing the IS model is too restrictive (why did patient S develop Paresis, because they have untreated syphilis even tho its only a 3% chance).

Casual Mechanical Model

Proposed by Wesley Salmon. Salmon argued that to explain an event scientifically, we should describe the actual chain of causes that produced it. This is called the causal-mechanical model. Instead of just showing that two things are statistically related, Salmon says we need to understand the real causal processes and interactions that led to the event. For example, in a cricket game, explaining why the ball changed direction would involve describing the physical interaction between the bat and the ball and the processes that followed. (Other alternative models include the Unification model and the Functional explanation)