R^2 is defined as:
R^2 = 1 - mean(e_1^2)/var(y_1)
where mean(e_1^2) is the mean of the squares of the residuals, and var(y_1) is the variance of the dependent variable that is being regressed. It isn't actually the square of any quantity!
R^2 can take values between 1 and -Infinity, and it will be negative whenever the residuals are larger than the residuals would be for the model y_1 ~ m.