1. Bias: Where does it lurk?

2. What ideas or words come to mind when you think of bias?
distortion
corruption

3. 2 areas where bias lurks…
At the “front end”
Research Design
What theory to build on?
What techniques to employ?
What information to gather?
What sampling strategy?
Towards the “back end”
Interpretation / Disclosure
Selection of cases
Relation to existing cases
Making “truth” claims
Presentation of data
experimenter interference (in the data)
projection (in the analysis)
context
history
limitations of human reasoning, e.g., confirmatory bias
theory (theoretical ideas influence the selection and interpretation of evidence as well as being tested against empirical data)
experimenter
sample (properly selected? big enough to permit any reliable conclusion?)
subject
design
conditions
apparatus
recording
reporting
Knowledge claims, intentions, beliefs, values, political/social context,
feasibility, inclinations, past experiences, etc.

4. Bias at the “front end” Example: What information to collect & how?
Challenges
Inclinations and preferences
Existence of previous solutions or models
Cognitive overload
Uncertainty
Wanting more measurable quantitative data over less measurable qualitative data
Wanting convergence towards implications
Perceptions of risks / benefits

5. Potential Pitfalls
Limiting the “space” of what information to collect and how to collect it
Reinforcing “satisficing” and “getting attached”
Focusing on factors perceived to be “controllable” (vs. those that exhibit some uncertainty)
Reducing disposition towards new ideas
Efforts to simplify restricting creative alternatives
Not questioning underlying reasons and assumptions

6. Bias at the “back end” Example: Interpreting ethnographic work
Interpretive work is
Flavored by intentions, beliefs and values
Politically cast and policy relevant
“In the conduct of fieldwork, methods and theory are so closely mixed with each other and with historically and socially contextualized relevancies that neutrality is relatively hard to come by.” (Katz, 2004, pg. 285)
Interpretive work should be not be assessed
“…outside a triangular appreciation of the empirical relationship between author, subjects, and readers.” (Katz, 2004, pg. 292)

7. Example: Bias in Interpretive Fieldwork (Katz, 2004)
Monolithic “theory singing” – politically and morally righteous theory
Failure to present variation by focusing on single (preferred) explanation
Refusal to be disciplined by the data
Morally sympathetic, yet superficial
Flat and unvaried
A goal: convey subtleties and nuances
Situation specific pictures of closely related data
Deliberately provocative comparisons
Multiple “angles”

9. Dealing with Bias… Many opportunities for bias in a study
Removing bias is unlikely, seek to minimize
Make it visible
Inform research design
Be disciplined by the data (interpretation)
Make it public
Disclosure to reader
Triangulate with subject
How knowledge claims can be made,
and how they can be validated