Philosophy of Science - Vocabulary Flashcards

Philosophy of Science — Comprehensive Study Notes (UST STS Slides)

• Purpose of notes: comprehensive summary of the slide deck for Philosophy of Science, focusing on core concepts, definitions, examples, and practical implications.

What is Philosophy?

• Philosophy defined as the love of wisdom.

  • Etymology: philo- love; sophos - wisdom -> Philosophy = love of wisdom.

  • Additional nuance: fascination with wisdom; knowledge gained from experiences.

  • Metaphor reference: “Wisdom teeth appears at a mature age” used as a playful reminder that wisdom often comes with maturity.

• Philosophy invites reflection on fundamental questions and the meaning of things in our experience.

Why do we need Philosophy?

• Philosophy embodies the love of knowledge gained from experiences and invites reflection on experience.

• It prompts questions such as:

  • What is being educated? (Student Philosophy)

  • What is the good life? (Personal Philosophy)

  • What is knowledge? What is the nature of learning? What is teaching? (Teaching Philosophy)

• Outputs:

  • Subjective or individual philosophies on different issues and situations.

Core branches of Philosophy (three traditional branches)

• Metaphysics

• Epistemology

• Axiology (and its sub-disciplines: Ethics and Aesthetics)

Metaphysics (What is the nature of reality?)

• Definition: “after physics”; deals with what cannot be observed in the physical environment; concerned with the reality of existence.

• Key subtopics:

  • Ontology: study of being; what exists; the nature of existence.

  • Cosmology: study of the universe as a whole; questions about origin and end of the universe; uses tools like the Hubble Space Telescope for cosmological research.

• Core questions:

  • What is real?

  • How do we know that what we see really exists?

• Examples used in slides: religion, soul, essence of reality.

• Brief relation to other branches: sets the stage for understanding what kinds of things can be known (epistemology) and what values or purposes they may serve (axiology).

Epistemology (What is the nature of knowledge?)

• Definition: theory of knowledge; focuses on knowledge and how it can be acquired.

• Role of logic: key dimension to epistemology; science as a method of correct processes of thinking or reasoning.

• Core ideas:

  • Differentiates between types and sources of knowledge.

  • Addresses how we justify beliefs and claims to knowledge.

• Core components:

  • Deductive Reasoning: general -> specific; logically true conclusions given true premises; example below.

  • Inductive Reasoning: specific -> general; conclusions based on patterns observed; may be probabilistic rather than certain.

• Concepts connected to epistemology:

  • Theory of knowledge: how knowledge is acquired, justified, and known.

  • The roles of evidence, reasoning, and justification.

• Visual aid from slides: lists of terms like hypothesis, theory, and law to distinguish levels of scientific explanation.

Axiology (What is the nature of values?)

• Explores values, worth, and value judgments.

• Subfields:

  • Ethics: studies the rightness or wrongness of human actions; what it means to be good; the concept of the good.

  • Aesthetics: studies beauty, art, and taste; explores the nature of beauty in general.

• Definition of axiology: study of values and how values arise in society; understanding meaning, nature, and origin of values and value judgments.

• Practical question: Why care for society? The role of empathy and motivation in action; variability depending on how people respond.

Philosophical Theories/Approaches in Science

• Overview: How scientists think about evidence, theory, and explanation (the slide set presents several theory-types and approaches).

• Core ideas summarized:

  • Theory vs. Hypothesis vs. Law:

  • Hypothesis: educated guess or proposed explanation for a phenomenon; starting point for investigation.

  • Theory: a well-supported set of hypotheses that have withstood testing; broader explanatory framework.

  • Law: a statement based on repeated observations, often with mathematical support, describing a relationship or regularity.

  • Inductivism (Inductive Reasoning): knowledge derived from observable facts; claims must be supported by observable evidence and patterns.

  • Deductive Reasoning: reasoning from general principles to specific conclusions; logical necessity if premises are true.

  • Hypothetico-Deductivism: proposes hypotheses and tests them through experimentation; emphasizes the testing of hypotheses and refinement of theories; often critiques the idea that all “facts” are directly observable.

  • Falsificationism: scientific progress rests on the ability to falsify hypotheses; theories are tentative and with time may be shown false by novel evidence.

  • Conjecture and Refutation: science progresses through open testing of theories and refuting preconceived notions; Kuhn’s paradigm concept is central here.

  • Paradigms and paradigm shifts: Normal Science vs Revolutionary Science; science moves through periods of normal inquiry and, at times, major paradigm shifts that redefine the framework of understanding.

• Thomas Kuhn reference: The Structures of Scientific Revolutions (1962) popularized the concept of paradigms and paradigm shifts.

Scientific Method (as presented in the slides)

• Core steps:

  • Ask a question / Define problem statement

  • Construct the hypothesis (hypothesize)

  • Test the hypothesis (experiment)

  • Collect the data (analyze and interpret)

  • Report the results

• Emphasis: the method is iterative and aims to build knowledge through systematic testing and evidence.

Types of Data in Research

• Quantitative data: numeric variables; questions like "How many?" or "How much?".

• Qualitative data: categorical variables; questions like "What type?" "From where?"; qualities; how often.

• Data collection methods: various approaches not detailed in slides, but the distinction guides how data is analyzed and interpreted.

Reliability and Validity in Measurement

• Reliability: consistency of a measurement method; same results under the same conditions.

  • Types:

  • Test-Retest Reliability (across time): consistency of results when the measurement is repeated over time.

  • Internal Consistency (across items): consistency of results across different parts of the test designed to measure the same thing.

  • Interrater Reliability (across researchers): consistency of results across different raters/observers.

• Validity: accuracy of the measurement; how well the method measures what it is intended to measure.

  • Types:

  • Face Validity: appears to measure the intended construct on its face (e.g., an IQ test).

  • Construct Validity: ensures the measure actually assesses the intended construct.

  • Content Validity: covers all aspects of the concept being measured (e.g., a comprehensive comprehension test).

  • Criterion Validity: results correspond to other valid measures of the same concept.

  • Discriminant Validity: scores do not correlate with measures of distinct variables (e.g., self-esteem should not mirror unrelated constructs).

• Relationship between reliability and validity:

  • A reliable measurement is not always valid (results may be consistent but not correct).

  • A valid measurement is generally reliable (if results are accurate, they should be reproducible).

How to Guard Against Misinformation (CRAAP Test)

• Currency: Is the information current?

• Relevance: Is the information important for your purpose?

• Authority: Who is the author/publisher/sponsor?

• Accuracy: Is the information supported by evidence? Are credible sources cited? Is it verifiable elsewhere?

• Purpose: What is the aim or bias behind the information?

Connecting to Real-World Science

• Science is described as based on facts (as a baseline principle) but the philosophy of science explores how we justify and validate those facts.

• Examples used in slides illustrate how theories are tested and revised:

  • Germ Theory of Disease as an example of a well-supported theory derived from observation and testing.

  • COVID-19 transmission examples illustrate falsification and updating beliefs in light of new evidence (droplets vs airborne).

  • The sun, disease, and other phenomena illustrate how observation leads to hypothesis and theory.

Practical Implications and Reflections

• The role of philosophy in science: clarifies what counts as knowledge, how we justify claims, and how values influence scientific inquiry.

• Ethical and practical implications: how we interpret data, design experiments, and communicate findings to society.

• Critical thinking skills: evaluating sources using CRAAP, distinguishing between hypothesis, theory, and law, and understanding the limits of observation.

Key Terms (glossary style)

• Philosophy: love of wisdom; inquiry into fundamental questions about reality, knowledge, values, and methods.

• Metaphysics: study of the nature of reality and existence; questions about what exists and what it means to exist.

• Ontology: branch of metaphysics dealing with the nature of being and categories of existence.

• Cosmology: study of the origin, structure, and future of the universe.

• Epistemology: study of knowledge and how we know what we know; inquiry into justification and acquisition of knowledge.

• Inductive Reasoning: reasoning from specific observations to general conclusions; often probabilistic.

• Deductive Reasoning: reasoning from general premises to specific conclusions; conclusions logically follow if premises are true.

• Axiology: study of values; includes Ethics and Aesthetics.

• Ethics: study of right and wrong, moral values, and judgments about conduct.

• Aesthetics: study of beauty, art, and sensory-emotional value.

• Theory: well-supported explanatory framework; broader than a single hypothesis.

• Hypothesis: educated guess about a phenomenon to be tested.

• Law (scientific): a statement based on repeated observations, often with mathematical formulation.

• Hypothetico-Deductivism: scientific approach that tests hypotheses through deduction and experimentation; emphasizes falsifiability and testing.

• Falsificationism: view that scientific progress comes from attempts to falsify theories; theories are inherently tentative.

• Conjecture and Refutation: ongoing process of forming conjectures and attempting to refute them, contributing to scientific progress.

• Paradigm: a dominant framework or set of assumptions guiding a scientific field; subject to revolution and paradigm shifts.

• Normal Science: routine work within an accepted paradigm; builds on existing knowledge.

• Revolutionary Science: phase where old paradigms are challenged and replaced by new ones.

• Reliability: consistency of measurement across time, items, or raters.

• Validity: accuracy of measurement in representing the intended construct.

• CRAAP: Currency, Relevance, Authority, Accuracy, Purpose — criteria for evaluating information quality.

Note: The slides repeatedly emphasize that the content is intended for UST STS students and may carry formatting remnants (e.g., typos). The essential ideas, definitions, and examples above capture the core concepts to study for the exam.