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 question What to avoid? Questions that imply answers dealing with different moral/ aesthetic values Questions whose answering involves unethical procedures Good questions: What proceeds (happens) why? Galileos 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 cant 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
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
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