Lecture 2: Research Logic and Research Design Flashcards

1
Q

Normative research

A
  • Questions that inquire what ought to be
  • deals with ethics, values, and value judgements
    Aim= prescriptive
  • Require the application of philosophy rather than of data
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2
Q

Positive research

A
  • Questions that inquire what is
  • Deals with empirical phenomena + theoretical concepts plus the link between them
  • Capable of being researched through data collection
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3
Q

Theoretical research

A
  • Theory elaboration, conceptualization
  • Analytical (truth = based on logical deductive reasoning)
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4
Q

Empirical research

A
  • Theory generation
    Testing + application,
    Conceptualization
  • Synthetic
    truth result from a confrontation between theory + empirical content
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5
Q

Descriptive research

kind of empirical research type

A

What is going on?

    • Collection of relevant facts that can be used as evidence in subsequent theory building or conceptualization
  • good descriptive research can lead to a ‘‘light bulb’ moment

Research objective: thick description, or conceptualization

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6
Q

Explanatory research

A

Why or How is it going on?

    • Can focus on causes of events (Y), causal effects (X) or causal mechanism (X-Y)
  • Why-questions: causal effects
  • How-questions: causal mechanism

Research objective: Theory building or theory testing

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7
Q

What is research design?

A

’’ a research design is** a logical plan for getting from here to there**, where here may be definited as the initial set of questions to be answered, and there is some set of conclusions (answers) about these questions)- Yin

    • Logic plan ‘’ a research design deals with a logical problem, not logistical’
      Not just about how you do the research, but also why and what the purpose of doing this is.
  • How are you going to conduct the research?
  • Methods need to be consistent and logical, not logistical
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8
Q

Units of variation

A

= units of analysis (count of N/ number of cases)

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9
Q

X- centered

A

Focuses on a cause
* has it a specific effect on a specific outcome
* gauging the contribution of X in explaining part of variation in Y

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10
Q

Case study

A

Empirical analysis of small sample of cases

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11
Q

Y- centered

A

Focuses on outcome.
* discern the relevant causes
* Explaining te variation in Y as best as you can (backward looking)

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12
Q

Mechanism-centered

A

Focuses on tracing a causal mechanism/ causal process
* Uncovering the sequence of intervening factors that link an X to an Y

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13
Q

What is a case?

A

Bounded empirical phenomenon that is an instance of population of similar empirical phenomena
* boundaries: spatial/ temporal/ substantive
* Causal homogeneity
Causal effects and mechanisms are expected to hold true for other cases in population

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14
Q

Why select cases purposefully

A
  • avoid selection bias + faulty generalizations
  • increases external validity
  • Random sampling is not usually an option due to the few cases or theoretical concerns.
  • Selecting cases carefully avoids false conclusions
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15
Q

Characteristics Case study

A
  • Generalizability: causal effects + mechanisms are expected to hold true for other cases in population
  • both qualitative as quantitative techniques can be used
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16
Q

Population

A

Universe of cases, class of events, studied +unstudied cases

17
Q

Sample

A

Studied cases

18
Q

Analytical level

A
  • Macro level
  • meso level
  • micro level
19
Q

Macro-level

A

Societies, economies, states

20
Q

Meso level

A

Groups, territorial subunits

21
Q

Micro level

A

Individuals

22
Q

Level of analysis

A
  • Cross-case level
  • Within-case level
23
Q

Cross-case level

A

Causal effects

24
Q

Within-case level

A

Causal mechanisms

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Types of observations
* Data set observations * Causal process observations
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Causation
A type of co-variation where one phenomenon contributes to or produces another
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Criteria for causal inference
* Temporal sequence ( X--> Y) * Proximity ( in time and space) * Constant coexistence (of X and Y) * Necessary connection (between X and Y)
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views towards causation
* Probabilisitc view * Deterministic view
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Probalistic view on causation
* When values of an independent variable increase or decrease --> this usually results in values of dependent variable increasing or decreasing * Cause as a pobability raiser = X sometimes effects Y
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Deterministic view on causation
when the values of an independent variable increase or decrease, this always results in the values of the dependent variable increasing or decreasing explanatory factors are (potentially) necessary and/or sufficient conditions for an outcome = X always effects Y
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What is a theory?
A theory consists of.. * A prime hypothesis * One or more explanatory hypotheses = argument * one or more antecedent conditions Theories provide an explanation as to how A causes B and they can be written in the form of an arrow diagram (theoretical model)
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A theory consists of
* a prime hypothesis A--> B * One or more explanatory hypotheses A--> q, Q-->r, r--> B = your argument * one or more antecedent conditions
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Predictive research
Predictions about future through identifying future patterns. Oriented towards elections. Not focused on in on the course
34
Choosing a Research design
* make decisions based on theory out there. * In explanatory research: you have to think about the variation you want to explain. * Level of analysis *The type of data you have to collect to answer your research question * Probabilistic or deterministic causational perspective * choice of methods
35
Theory testing
1. Start with describing/ analysing theory. 2. Hypotheses 3. Measurement/ sampling etc 4. Data collection 5. Data analysis 6. Either data analysis makes it so there are implications for hypothesis; so either confirm/ reject theory. When you reject; a new theory is needed. Deductive --> when theory-testing * Describing/analyzing theory. * Formulating hypotheses, measurement, and data collection. * Data analysis leading to hypothesis confirmation or rejection.
36
Theory building
When there is not much or no theory to build on. 1. Start with data collection 2. Data analysis 3. Implications for new hypothesis/ theory 4. When implications for hypothesis, it results in a theory 5. When new theory is needed, a new hypothesis is needed and then you go through the process of measurement, data collection, data analysis, implications hypothesis again, and making hypothesis in the end
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Types of Research designs
1. Single case --> short time + space ( one case in time) 2. Comparative case study--> different case studies at a specific time point 3. Periodisation study --> one case across different points in time
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Brainstorm qualitative research questions?
* List political science or international relations terms * HIghlight complex processes, beliefs, opinions or motivations * Create research questions by associating themes, often starting with ''how'' why?'