People who believe they contribute to society are more likely to vote and engage in politics. They were also more likely to donate to and volunteer for political causes compared to individuals who saw their contribution to society as smaller.

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The N-closest or N-best dithering algorithm is a straightforward solution to the N-candidate problem. As the name suggests, the set of candidates is given by the closest palette colours to the input pixel. To determine their weights, we simply take the inverse of the distance to the input pixel. This is essentially the inverse distance weighting (IDW) method for multivariate interpolation, also known as Shepard’s method. The following pseudocode sketches out a possible implementation:

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