GSSRResearch Methodology and Methods of Social Inquiry socialinquiry.wordpress.comJanuary 24, 2012

Summary

Formulation of Theoretical Model & Research Problem (1)

THE POSSIBILITY OF SURPRISE IN SOCIAL RESEARCH; RESEARCH PROBLEM AS A PUZZLE

Selecting Research Questions

– difference btw. advocacy research & scientific research

(Advocacy research refers to research that sifts through evidence to argue a predetermined position)

(Scientific research does not suppress contrary/ inconvenient

evidence)

Formulation of Theoretical Model & Research Problem (2)

Researchable questionWhat to avoid?

Questions that imply answers dealing with different moral/ aesthetic values

Questions whose answering involves unethical procedures

Good questions:What proceeds (happens) why? Galileo’s maxim: description first, explanation second

– Proposing new research– Challenging prior research– Extending prior research

Formulation of Theoretical Model & Research Problem (3)

Interesting question“The heart of good work is a puzzle and an idea” (Abbott 2003, p. xi).

The no-surprise objection: “the answer is already well documented”, “we know answer before we do research” “the question is trivial”

The “so what” objection: “no relevance for social theory/ for social life”

Choosing variables & specifying hypotheses

At minimum, any hypothesis involves 2 variables: an independent variable & a dependent variable.

“You can’t explain a variable with a constant.” Maximize variance to find the effect of a cause

Preparation of Research Design (1) A research design is a plan that shows, through a discussion of the

model and data, how we expect to use our evidence to make inferences.

Model implies variables, units, & observations (values)

Data collection

- refers to observation, participant observation, intensive interviews, large-scale surveys, histories recoded from secondary data, ethnographies, randomized experiments, and other types.

Preparation of Research Design (2)

How will/are the data collected?

Decisions: What data are available? What additional data will be needed?

We have to know how the data will be used Discussion of data analyses methods

Multi-method approaches

Measurement

Criteria of good measurement:

• Valid

• Reliable

• Exhaustive

• Mutually Exclusive

All involve measurement errors

Observed reality = True reality + Error

Minimizing errors through multi-indicator approach

Sampling

Coverage Error

Sampling Error

Non-responese Error

Data collection

Politics of data collection

Data collection as a social process.

Sociology of data collection: Who needs what data for what purpose?

Quality control of data collection

Processing the Data: Analyses & Interpretation

Statistics & substance in causal inferences

Special issues of causal inferences:

- endogeneity

- types of errors

– Type I (α): reject the null hypothesis when the null hypothesis is true

– Type II (β): accept the null hypothesis when the null hypothesis is false

Glenn Firebaugh, 2008. Seven Rules for Social Research. Princeton: Princeton University Press

1. THE POSSIBILITY OF SURPRISE IN SOCIAL RESEARCH. RESEARCH PROBLEM AS A PUZZLE

2. LOOK FOR DIFFERENCES THAT MAKE A DIFFERENCE, & REPORT THEM

3. BUILD REALITY CHECKS INTO YOUR RESEARCH

4. REPLICATE WHERE POSSIBLE

5. COMPARE LIKE WITH LIKE

6. USE PANEL DATA TO STUDY INDIVIDUAL CHANGE & REPEATED CROSS-SECTIONAL DATA TO STUDY SOCIAL CHANGE

7. LET METHOD BE THE SERVANT, NOT THE MASTER