Mcquire, W. J. The Yin and Yang of progress in social psychology. JPSP, 26, 1973, 446-456

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Paradigms in social psychology

The old paradigm
Creative aspect: derive our hypotheses from current theoretical formulations.
Crititcal aspect: manipulational experiments in a laboratory.

Attacks
Argument that hypthoses should be formed for relevance to social problems than relevance to theoretical issues.

Argument that laboratory manipulation is full of artifacts (experimenter bias, demanc character, evaluation apprehension, etc.). Trend toward field studies and correlational analysis from natural settings.

Recent paradigm
1. Derive new hypotheses from adhoc interest or social relevance.
2. Test with correlational anslysis in natural settings.

Critique of Recent paradigm
1. Too simplistic (hypotheses based on linear models), fail to address the complexities in normal situations.

2. New testing methodologies are inadequate too.
"we social psychologists have tended to used the manipulational laboratory experiemnt not to test our hypotheses but to demonstrate their obvious truth."

We usually test what we believe is already true, and blame the testing method if we get a different answer and retest with different conditions until we match our preconcieved notions.

Issues with the New Field Paradigm
1. We're not really testing our hypotheses out in the field. Rather than testing our "stage manager" abilities, we're testing our "finder" ability. If our hyptheses is not proven in field testing, we assume that field testing is inadequate and look for a simpler field to test again.

My Expectattions of New Paradigm
1. Hypotheses will reflect complexities and multivariates
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Proposed tactical changes to aid shift to future paradigm.
1. We should emphasize the hypthosis formulation stage over the hypothesis testing stage. Currently more focus is on test methodology. Some hypthesis formulation examples are case study, paradoxical incident,analogy (like with biological processes), hypothetico-deductive (put parts of commonsensical principles together to form new predictions), functional analysis , practitioner's rules of thumb. Another is trying to account for conflicting results. Another is accounting for exceptions in general findings. Another is reducting complex relationships to simpler component relationships.

2. Think complexly, with conceptual models of parallel processing, feedback loops, etc.

3. Observe people not data. Data often just shadows of reality.

4. We need social archives, time series data (repeated tests over time).

5. Move from simple statistical anslysis to multivariate analysis, time series analysis, interval scaling of qualitative data.

6. Learn to be frugal with research money. Cut out waste and repetitious studies.