Research Design

Question 1

What is research design? (Aim, Controversy, Positivist)

Answer 1

Aim: Expand boundaries of existing knowledge.
Controversy: Interpretive knowledge.
Positivist: Broad research of causal things.

Question 2

Objective: Why do we conduct research?

Answer 2

Obtain valid answers reliably and efficiently.
Between epistemological and methodological approaches.
Applied (operational) epistemology – understanding how we know.

Question 3

Levels of Generality, Level 1

Answer 3

Ontological, epistemological, broad theoretical outlook.
Explicit, not implicit.
Types: Ask about them.

Question 4

Levels of Generality, Level 2

Answer 4

Research goal, question, theory relation, conceptualization, methodology.
Identifying characteristics of theoretical outlook.

Question 5

Levels of Generality, Level 3

Answer 5

Cases, variables, evidence.

Question 6

How do we identify a gap in our knowledge?

Answer 6

Recognizing absence in existing knowledge.

Question 7

What is the general aim of research?

Answer 7

Advance the ‘state of the art.’
Motivation: Puzzles, lacunae, substantive problems.

Question 8

When does theory come into play?

Answer 8

Guides operationalization, conceptualization.
Essential for behavioralist, large statistical methodology.

Question 9

Is research methodology solely dependent on research questions?

Answer 9

Example: Investigating Trumpism may involve elite interviews, discourse analysis.

Question 10

Experimental vs. Observational Designs: Why can’t social sciences often mimic laboratory experiments?

Answer 10

Complexity, ethical reasons.
Observational designs in political science.

Question 11

What does the researcher control in observational methods?

Answer 11

Cases to study, number of cases, features to observe, data to collect.
Qualitative methods when quantitative is not available.

Question 12

What is the first step in theory development?

Answer 12

Abstract, unobservable concepts.
Contestation, inductive element.
Operationalization follows conceptualization.

Question 13

How does the choice of N impact research design?

Answer 13

Large-N: Positivist designs, causality.
Small-N: Interpretivist designs, understanding phenomena.

Question 14

When is the comparative method preferred?

Answer 14

Focus on small-N case studies.
Alternative when experimental or statistical methods are not feasible.

Question 15

How does MDSD work?

Answer 15

Find somewhat similar cases with different outcomes.
Identify common conditions, nuance understanding.

Question 16

When is MSSD used?

Answer 16

Investigate positive and negative cases.
Identify differing conditions for outcomes.

Question 17

What are general limitations of MDSD & MSSD?

Answer 17

Sensitive to case selection/variable specification.
Limited cases, potential bias in theory testing.

Question 18

When are single case studies appropriate?

for what is it for?

Answer 18

If MDSD/MSSD not possible.
Comparative analysis important for understanding and explanation.

Question 19

(Scientific) Description Analytical Dimensions:

Answer 19

Theoretical influence on concepts.
Constructed nature of research concepts.

Question 20

(Scientific) Description Implications:

Answer 20

For empirical and normative theory.

Question 21

(Scientific) Description Representation:

Answer 21

Comprehensive representation of one/few cases (many variables) OR
Classification of many cases (one/few variables).

Question 22

(Scientific) Description Description and Classification:

Answer 22

Description aligns with classification.
Value: Selecting analytical dimensions for empirical projection.

Question 23

(Scientific) Description Classifications in Social/Political World:

Answer 23

Relative and more or less accurate.
First step to theory; somewhat unnatural.
Classifications cannot be neutral.

Question 24

(Causal) Explanation Associated with Foundationalist Ontologies:

Answer 24

Behavioralist, rational choice, Marxist, institutionalist approaches.

Question 25

(Causal) Explanation Probabilistic Nature:

Answer 25

Not deterministic but probabilistic.
Example: Sibling A going to uni doesn’t determine voting choices for Sibling B.

Question 26

(Causal) Explanation Causal Mechanism:

Answer 26

Understanding the process.
Strength of causal effect.

Question 27

(Causal) Explanation Retrospective vs. Prospective:

Answer 27

Analyzing what was vs. predicting what would be.

Question 28

Interpretation Seeking Understanding:

Answer 28

Associated with anti-foundationalist ontologies.
Embraced by constructivist and some feminist theoretical approaches.

Question 29

Interpretavist thought of Scientific Causation:

Answer 29

Interpretivists reject a ‘scientific concept of causation’ (Bevir and Rhodes 2016).
Emphasis on critical standpoint.

Question 30

Interpretation Political Actions:

Answer 30

Result from subjective reasons, meanings, and beliefs.
Focus on understanding rather than explanation (Weber).

Question 31

Interpretation of Constitutive Arguments

imply what to come about?

Answer 31

Emphasis on constitutive rather than causal arguments (Wendt).
Implying that something is to come about.

Question 32

Theory Development:

Answer 32

Involves theory generation, testing, etc.
Plays a role in operationalization and conceptualization.

Question 33

Behavioralist Approach:

Answer 33

Guides operationalizing and conceptualizing.
Utilizes large statistical methodology.