Fig. 5: Study 3a, norm vs minimal pay condition in India and the United States.

Effects of a minimal monetary incentive (of 1 cent per 20 image ratings; green) and a social norm condition (blue) in the United States (N = 382 participants recruited on Prolific) and India (N = 352 participants recruited on MTurk). a, The central tendency and distribution of effort by incentive and country. The black line within each box represents the median and the red dot shows the mean; upper and lower bounds show the third and first quartiles, respectively; whiskers represent 1.5× the interquartile range, with black dots showing observations outside of this range. The width of each violin corresponds to the frequency of observations at any given number of images rated on the y axis. The interaction between country and incentive in a multiple linear regression model is statistically significant (b = 13.77, t(726) = 2.31, P = 0.021, 95% CI 2.09–25.45). b. The money advantage, that is, how much more effective the minimal incentive is compared to the social norm condition in each country. c, The central tendency and distribution of cost-effectiveness (effort per dollar spent) of each incentive by country. Graph elements are analogous to those in a, with the width of each violin corresponding to the frequency of observations at any given level of cost-effectiveness (effort per dollar spent) rated on the y axis. Minimal monetary incentive is significantly more cost-effective than the social norm condition in the United States (two-sided Welch’s t(365.20) = 3.14, P = 0.002, P_Bonf = 0.004, Mean_difference = 13.00, d = 0.32, 95% CI 4.86–21.15) but not in India (two-sided Welch’s t(345.72) = −0.27, P = 0.785, P_Bonf = 1.000, Mean_difference = −1.06, d = −0.03, 95% CI −8.73 to 6.60). In b, error bars are bootstrapped 95% CIs for the mean relative difference in the number of images rated in the minimal-monetary-incentive vs social norm condition.