Introduction to Comparative Politics, Falsifiability, and Theory Testing

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Fundamental Definitions of Politics and Science

• Politics:

  • The subset of human behavior that involves the use of power or influence.

  • Occurs when an individual or group attempts to influence others to take an action, or attempts to free themselves from the influence of another person or group.

• Science:

  • A method for understanding and explaining the world that emphasizes the use of statements that are falsifiable.

  • Falsifiable statements are those that can be empirically examined to determine if they are wrong or false.

• Comparative Politics:

  • The subfield of political science that focuses primarily on politics within countries or states, or compares political phenomena across countries and states.

Classifying Human Behavior: Practical Examples of Politics

• Scenario 1: Senator Trading Votes:

  • Scenario: A senator trades her vote on a controversial bill in exchange for support on a local highway project.

  • Classification: Politics.

  • Explanation: A legislative vote represents political power within a deliberate institution, used to exert influence over another actor to achieve a specific outcome.

• Scenario 2: Roommates Arguing Over a Thermostat:

  • Scenario: Roommates argue over who controls the apartment thermostat, and one threatens to stop paying their portion of the utility bill.

  • Classification: Politics.

  • Explanation: Exerting power by withholding financial contributions to force another individual to comply with a preference constitutes political influence within a non-governmental context.

• Scenario 3: Professor Setting a Grading Curve:

  • Scenario: A professor sets a grading curve for an academic course.

  • Classification: Politics.

  • Explanation: Involves an institutional authority exercising power and structural influence over a group of individuals.

• Scenario 4: Natural Disasters (Hurricane Destroying a Coastal Town):

  • Scenario: A hurricane strikes and destroys a coastal community.

  • Classification: Not politics in itself; however, governmental responses are political.

  • Explanation: A hurricane is a natural occurrence, not a subset of human behavior. However, government preparation, relief distribution, and political responses to the disaster represent political processes determining "who gets what, when, and how."

• Scenario 5: Going for a Solo Run:

  • Scenario: An individual goes for a solo run on a Saturday morning.

  • Classification: Context-dependent (Generally Not Politics).

  • Explanation: If an individual exercises complete control over their time without needing to negotiate or exert influence over others (e.g., arranging childcare or household duties), it is not politics. If it requires bargaining power over household responsibilities, it enters the realm of politics.

The Five Steps of the Scientific Method

• Step 1: Identify a Question or Puzzle:

  • Formulate a research question focused on unexplained, counterintuitive, or troubling observations in the world.

• Step 2: Formulate a Theory:

  • Develop a logical model, explanation, or argument that provides a answer to the question.

• Step 3: Derive Implications (Hypotheses):

  • Deduce specific observations or expectations that must logically follow if the theory is correct.

• Step 4: Test Hypotheses:

  • Collect empirical data from the real world to examine whether the predicted implications are observed.

• Step 5: Evaluate the Theory:

  • Assess whether the theory is falsified (rejected) or corroborated (failed to be disproved) based on empirical evidence.

Step 1: Formulating Good Comparative Politics Questions

• Characteristics of Strong Political Science Questions:

  • Formatted primarily as "why" or "what if" questions.

  • Focus on troubling, unexpected, or puzzling patterns (e.g., why citizens vote for leaders who dismantle democratic institutions despite preferring democracy).

  • Rooted in real-world empirical observations rather than purely hypothetical or fictional scenarios.

• Examples of Research Questions:

  • State Strength: Why are some states stronger than others?

  • Democratic Backsliding: Why do citizens vote for politicians who dismantle democratic institutions?

  • State Repression: Do public protests increase or decrease following state repression?

  • Party Systems (Sabine): Why do some countries have a hyper-fragmented party system while others have only five or six main political parties?

  • Governmental Structure (Patty): Is a strong, unified government necessary for policy stability?

  • Comparative Healthcare Policy: Why do countries like Canada and Mexico possess universal healthcare systems while the United States relies primarily on private health insurance?

  • State Formation: Why are some countries undergoing international turmoil still able to establish stable functional governments?

Step 2: Scientific Theories and Logical Models

• Definition of a Scientific Theory:

  • A logically consistent set of interconnected statements that explains why an observed phenomenon occurs.

  • Interchangeably referred to as a model or an explanation.

  • Typically causal, linking an independent or explanatory variable ($X$) to a dependent or outcome variable ($Y$) through a specific mechanism.

• The Map Analogy of Theories:

  • A theory functions like a subway map (e.g., the New York City Subway map).

  • A subway map abstracts reality by intentionally omitting extraneous details (such as the location of every store or building) to focus exclusively on essential connections needed for navigation.

  • Similarly, a theory simplifies complex social reality to highlight fundamental causal mechanisms without incorporating every confounding variable.

• Generalizability versus Historical Context:

  • Theories seek to uncover general underlying laws of human and political behavior.

  • While theories can incorporate temporal or historical constraints (e.g., international incentives for democracy that existed between the end of the Cold War and recent history), their core logical framework should apply across comparable cases.

Falsifiability and Categories of Non-Falsifiable Statements

• Principle of Falsifiability:

  • To be scientific, a statement or theory must be inherently testable such that there is a logical possibility of observing empirical evidence that refutes it.

• Categories of Non-Falsifiable Statements:

  1. Tautologies:

     • Statements that are true by definition and cannot be empirically disproved.

     • Mathematical Example: "Triangles have three sides."

     • Political Science Example: "Backlash protests occur because states suppress." If backlash protests are explicitly defined as protests caused by state repression, the statement is a tautology and cannot be falsified.

  2. Unobservable or Metaphysical Phenomena:

     • Claims regarding non-empirical, supernatural, or unmeasurable concepts.

     • Example: "God exists."

     • Explanation: This claim relies on faith and lies beyond empirical observation or measurement using scientific tools; it cannot be falsified in this life.

  3. Value Judgments and Normative Claims:

     • Statements evaluating morality, ethics, or intrinsic worth.

     • Example: "The unethical life is not worth living."

     • Explanation: Normative evaluation cannot be disproved through empirical data collection.

• Falsifiable Claim Example:

  • Statement: "Democracies are less likely to go to war than dictatorships."

  • Evaluation: Falsifiable. We can define war and regime types, collect empirical historical data, and test whether democracies engage in conflict at lower rates.

Logic of Hypothesis Testing: Categorical Syllogisms

• Structure of Conditional Arguments:

  • A categorical syllogism consists of a Major Premise, a Minor Premise, and a Conclusion.

  • Major Premise Format: "If $P$, then $Q$"

    • $P$ is the Antecedent (representing the theory: "Theory $T$ is correct").

    • $Q$ is the Consequent (representing the implication: "Implication $I$ is observed").

• Set Theory Visual Representation:

  • The conditional statement "If $P$, then $Q$" means the set $P$ is entirely contained within the set $Q$.

  • Being inside $P$ guarantees being inside $Q$, but being inside $Q$ does not guarantee being inside $P$

• The Four Logical Forms of Conditional Arguments:

  1. Affirming the Antecedent:

     • Major Premise: If $P$, then $Q$.

     • Minor Premise: $P$ is observed (Affirms $P$).

     • Conclusion: Therefore, $Q$ is true.

     • Validity: Valid argument.

     • Logic: If we are inside set $P$, we must be inside set $Q$

  2. Affirming the Consequent:

     • Major Premise: If $P$, then $Q$.

     • Minor Premise: $Q$ is observed (Affirms $Q$).

     • Conclusion: Therefore, $P$ is true.

     • Validity: Invalid argument (Logical fallacy).

     • Logic: An observation can lie in the region of set $Q$ that is outside set $P$. Observing $Q$ does not establish that $P$ occurred.

  3. Denying the Antecedent:

     • Major Premise: If $P$, then $Q$.

     • Minor Premise: Not $P$ is observed (Denies $P$).

     • Conclusion: Therefore, Not $Q$ is true.

     • Validity: Invalid argument (Logical fallacy).

     • Logic: Even if $P$ does not occur, $Q$ can still occur via alternative causes.

  4. Denying the Consequent:

     • Major Premise: If $P$, then $Q$.

     • Minor Premise: Not $Q$ is observed (Denies $Q$).

     • Conclusion: Therefore, Not $P$ is true.

     • Validity: Valid argument.

     • Logic: Because set $P$ is entirely enclosed within set $Q$, failing to observe $Q$ guarantees that $P$ cannot have occurred.

The Asymmetry of Science: Why Theories Cannot Be Proven

• Application to Theory Testing:

  • Theory Testing Framework:

    • Major Premise: If Theory $T$ is correct, then Implication $I$ will be observed.

• The Fallacy of Confirmation (Affirming the Consequent):

  • If we observe Implication $I$ in empirical testing, concluding that Theory $T$ is true uses the logical form:

    • If $T$, then $I$

    • $I$

    • Therefore, $T$

  • Because Affirming the Consequent is an invalid logical argument, a scientific theory can never be proven true by confirming its implications.

  • Alternative, unexamined theories could explain the observation of Implication $I$

• The Logic of Disconfirmation (Denying the Consequent):

  • If we fail to observe Implication $I$ in empirical testing, concluding that Theory $T$ is false uses the logical form:

    • If $T$, then $I$

    • Not $I$

    • Therefore, Not $T$

  • Because Denying the Consequent is a valid logical argument, a scientific theory can be logically falsified by refuting its implications.

• Fundamental Asymmetry of Science:

  • There is a fundamental logical asymmetry between confirming and disconfirming empirical observations.

  • Scientific knowledge is inherently tentative and subject to revision.

  • As highlighted by philosopher of science Karl Popper, science advances exclusively by attempting to falsify theories, never by proving them definitively.

  • Real-World Analogy: Public frustration with shifting health guidance (e.g., COVID-19 mask recommendations) reflects this fundamental scientific process—conclusions change when hypotheses are disproven by new empirical evidence.

Deductive versus Inductive Approaches

• Deductive Reasoning:

  • An approach that begins with a theoretical model, derives logical implications (hypotheses), and then collects empirical observations to test those implications.

  • Top-down structure: Theory $\rightarrow$ Implications $\rightarrow$ Data Collection $\rightarrow$ Evaluation.

  • Primary method used for formal theory testing.

• Inductive Reasoning:

  • An approach that begins with specific real-world empirical observations and works backward to generate a generalized theory that explains the patterns observed.

  • Bottom-up structure: Data/Observation $\rightarrow$ Pattern Recognition $\rightarrow$ Theory Formulation.

  • Primary method used by social scientists for theory generation.

Necessary and Sufficient Conditions

• Necessary Conditions:

  • A condition $X$ that must be present for outcome $Y$ to occur.

  • Logic: If $Y$ occurs, then $X$ must have been present ($Y \rightarrow X$). Without $X$, $Y$ cannot occur.

  • Physical Example: Oxygen is a necessary condition for fire. Fire cannot exist without oxygen, though the presence of oxygen does not guarantee fire.

  • Political Science Example: Having a military is a necessary condition for a military coup.

• Sufficient Conditions:

  • A condition $X$ that is enough by itself to guarantee outcome $Y$

  • Logic: If $X$ occurs, $Y$ will inevitably occur ($X \rightarrow Y$).

  • Physical Example: Jumping is a sufficient condition to leave the ground. Jumping guarantees leaving the ground, but leaving the ground can occur through other means (e.g., flying, being lifted).

• Set Relationship Summary:

  • For a Necessary Condition, outcome $Y$ is a subset of condition $X$

  • For a Sufficient Condition, condition $X$ is a subset of outcome $Y$

Application: Economic Crisis and Democratic Breakdown

• Evaluating Economic Crisis as a Condition for Breakdown:

  • Research Question: Is an economic crisis a necessary or sufficient condition for democratic breakdown?

  • Student Debate Summary:

    • Allison: Economic crisis is not necessary because democracies can break down without economic hardship; it might be sufficient.

    • Anton: Economic crisis is not sufficient because many economic crises occur without causing democratic breakdown.

    • Joe and Rosa: Raised issues regarding the definitions of breakdown and context.

• Definitive Conclusion:

  • An economic crisis is neither necessary nor sufficient for democratic breakdown.

  • Why it is NOT necessary: Democratic breakdowns occur in the absence of economic crises (e.g., democratic backsliding in Poland occurred during a period of strong economic performance).

  • Why it is NOT sufficient: Severe economic crises often occur without triggering democratic collapse (e.g., Greece maintained its democratic institutions despite a catastrophic financial crisis).

• Limits of Necessity and Sufficiency in Political Science:

  • Very few political relationships meet the rigid standards of necessary or sufficient conditions due to the complexity of the social world.

  • Necessary conditions in political science are often trivial or obvious (e.g., having a military is necessary for a military coup).

  • Political scientists rely on probabilistic, correlational, and associative relationships rather than deterministic rules.

  • Example 1: High economic development is strongly correlated with democratic stability, but exceptions exist.

  • Example 2: Dependence on oil wealth is a strong predictor of authoritarianism, but non-authoritarian nations with vast oil wealth exist (e.g., Norway).