Evidence does not support the claim that observers universally recognize basic emotions from signals on the face. The percentage of observers who matched the face with the predicted emotion (matching score) is not universal, but varies with culture and language. Matching scores are also inflated by the commonly used methods: within-subject design; posed, exaggerated facial expressions (devoid of context); multiple examples of each type of expression; and a response format that funnels a variety of interpretations into one word specified by (...) the experimenter. Without these methodological aids, matching scores are modest and subject to various explanations. (shrink)

We used multiple methods to examine two questions about emotion and culture: (1) Which facial expressions are recognised cross-culturally; and (2) does the “forced-choice” method lead to spurious findings of universality? Forty participants in the US and 40 in India were shown 14 facial expressions and asked to say what had happened to cause the person to make the face. Analyses of the social situations given and of the affect words spontaneously used showed high levels of recognition for most of (...) the expressions. A subsequent forced-choice task using the same faces confirmed these findings. Analysis of the pattern of magnitude, discreteness, and similarity of responses across cultures and expressions led to the conclusion that there is no neat distinction between cross-culturally recognisable and nonrecognisable expressions. Results are better described as a gradient of recognition. (shrink)

Sections include: experiments and generalised causal inference; statistical conclusion validity and internal validity; construct validity and external validity; quasi-experimental designs that either lack a control group or lack pretest observations on the outcome; quasi-experimental designs that use both control groups and pretests; quasi-experiments: interrupted time-series designs; regresssion discontinuity designs; randomised experiments: rationale, designs, and conditions conducive to doing them; practical problems 1: ethics, participation recruitment and random assignment; practical problems 2: treatment implementation and attrition; generalised causal inference: a grounded theory; (...) generalised causal inference: methods for single studies; generalised causal inference: methods for multiple studies; a critical assessment of our assumptions. (shrink)