POLS-260 midterm

Major Characteristics of Social Science as a Method of Inquiry

  • 1. Non-Normative

    • Definition: Objective, as opposed to subjective.
    • Avoids value judgments about research topics and findings.

  • 2. Empirical

    • Definition: Utilizes replicable observations of facts as evidence.
    • Purpose: Tests, evaluates, and verifies claims to knowledge and truth.

  • 3. Public

    • Definition: Promotes scrutiny and comment on research design, methods, theories, hypotheses, evidence, and conclusions.

  • 4. Provisional

    • Definition: Recognizes that future research may refute current, tentative assumptions and findings.

  • 5. Explanatory

    • Definition: Seeks explanations for why an observed event or development has occurred, beyond mere description.

  • 6. Cumulative and Generalizable

    • Definition: Knowledge and understanding build over time and across disciplines, enhancing cross-applicability.

Major Assumptions of Empiricism

  • 1. Sensory Experience as Sole Source of Knowledge

    • Analogy: John Locke’s tabula rasa - the human mind at birth is like a blank slate shaped solely by sensory experience.

  • 2. Subject/Object Dichotomy

    • Definition: Two realms of reality exist that are distinct; the subject inhabits an independently existing world of objects and processes.

  • 3. Clear Connection Between Subject and Object

    • Definition: Accurate connections can be established using the five senses without distortion.

  • 4. Fact/Value Dichotomy

    • Definition: The distinction between “Is” (facts) and “Ought” (values) must be maintained in interactions with the objective world; facts are verifiable, while values are not.

Application of Empiricist Concepts by Popper and Skinner

  • Karl Popper

    • Key Concepts:
    • Verification by Falsification: Involves attempting to disconfirm or disprove claims to search for truth.
    • Hypothetical-Deductive Method: Involves proposing hypotheses for testing against relevant evidence, aiming to falsify them. Hypotheses that withstand falsification are retained for further investigation.

  • B.F. Skinner

    • Approach:
    • Asserts that human behavior exhibits regularities that conform to observable orders, making the scientific study of human behavior viable. Controlled observation and manipulation of behavior are feasible and desirable.

Validity and Reliability in Research Process

  • Validity

    • Definition: "The extent to which a measurement records the true value of the intended characteristic and does not measure unintended characteristics."
    • Importance: A valid measure minimizes systematic error.

  • Reliability

    • Definition: The consistency of measures concerning our concepts; seeks to minimize random error.
    • Priority: Higher priority should be given to validity over reliability.

  • Quantitative Bias

    • Definition: Persistent problems in social science research characterized by the use of reliable measures while ignoring valid qualitative aspects of concepts.

Levels of Measurement

  • 1. Nominal Level

    • Definition: A name or label for a category of variables/data; no direction or amount.
    • Example: Gender, race, or region.
    • Characteristics: Categories must be exhaustive and mutually exclusive.

  • 2. Ordinal Level

    • Definition: Variables/data indicate more or less of an amount or direction but lack a precise scale of measurement.
    • Example: Likert scales or surveys assessing attitudes and opinions.

  • 3. Interval Level

    • Definition: Variables/data possess an amount or direction with a precise scale. Expressed in real numbers with equal spacing.
    • Example: SAT scores, Lexile scales.

  • 4. Ratio Level

    • Definition: Meets all interval criteria plus contains a meaningful zero value, enabling calculation of ratios between observations.
    • Example: Murder rate per 100,000 people.

Measures of Central Tendency

  • Purpose of Measures

    • Measures of central tendency summarize important characteristics of data observations.
    • Types: Mode, Median, Mean.

  • Mode

    • Definition: The value that occurs most frequently in a dataset.
    • Applicability: Used at all four levels of measurement, but specifically the only measure appropriate for nominal data.

  • Median

    • Definition: The middle value where 50% of observations lie above and below.
    • Applicability: Can be used with ordinal, interval, and sometimes ratio-level data.

  • Mean

    • Definition: Calculated by summing all values in a dataset and dividing by the number of cases.
    • Example: For a dataset with 16 entries, the mean is calculated by summing all entries and dividing by 16.

  • Measures of Dispersion

    • Range
    • Definition: Basic measure of dispersion suitable for ordinal and ratio-level data; calculated by subtracting the lowest value from the highest value.
    • Implication: Large ranges indicate more variation.
    • Standard Deviation
    • Definition: Precise measure of dispersion indicating average deviation from the mean in a dataset.

Cause-and-Effect Relationship in Research

  • Definition

    • The relationship observed between changes in the independent variable (IV) that brings about changes in the dependent variable (DV).

  • Five Criteria for Establishing Cause-and-Effect

    1. IV and DV must change together (association, correlation).
    2. Change in IV must precede or coincide with changes in DV.
    3. A logical connection must link IV and DV plausibly.
    4. The relationship must be consistent with other evidence.
    5. The IV proposed must be significant compared to other factors affecting the DV.

  • Common Problems for Social Scientists

    • Intervening Variables: Variables that occur between IV and DV, impacting their relationship.
    • Antecedent Variables: Pre-existing variables that affect both IV and DV.
    • Spurious Relationships: Apparently causal relationships due to one or more antecedent variables that can mislead researchers into inferring cause and effect (Pollock, p.137).

Hypothesis Testing Process

  • Definition of Hypothesis

    • A testable statement about the empirical relationship between IV and DV (Pollock, p.82).

  • Null Hypothesis

    • Definition: A hypothesis stating that no relationship exists between the given IV and DV (Box 3.1, p. 84).

  • Testing Process

    • Researchers do not test their hypotheses directly. They aim to accept or reject the null hypothesis.
    • If the null hypothesis is accepted, the original hypothesis is deemed “not supported by the evidence.”
    • If the null hypothesis is rejected, the original hypothesis is considered “provisionally true.”

Relationship Between Variables in Cross-Tabulation

  • Finding Relationships

    • Identification of the independent (IV) and dependent variables (DV): e.g., IV is self-identification and DV is attitudes towards homosexuality.

  • Overall Pattern

    • Summary of observed relationships represented in the cross-tabulation table based on column and row interpretations.

  • Column and Row Interpretations

    • Column values indicate IV characteristics.
    • Row values reflect DV observations.

Research Application Strategies

Research Question 1
Does the presence of racist attitudes among individual Americans affect their views concerning the issue of gun control?

  • Concepts
    • 1. Racist attitudes: Perceptions of others.
    • 2. Gun control views: Opinions on government regulations regarding firearms.
  • Variables and Indicators
    • Indicators: Responses to questionnaires, surveys, blogs; memberships in activism groups.
    • Data can be found by analyzing responses to blog entries and associated campaigns.

Research Question 2
To what extent do the religious beliefs of Americans affect their attitudes toward same-sex marriage? What effect might age have on this relationship?

Research Question 3
Is a country’s standard of living related to its military strength?

  • Concepts and Variables
    • 1. Military strength: Types of resources, such as transportation, manpower, weapons, territories, and financial resources.
    • 2. Standard of living: Income, housing, education, and healthcare.