Notable mean score differences for the "e-rater"® automated scoring engine and for humans for essays from certain demographic groups were observed for the "GRE"® General Test in use before the major revision of 2012, called rGRE. The use of e-rater as a check-score model with discrepancy thresholds prevented an adverse impact on the examinee score at the item or test level. Despite this control, there remains a need to understand the root causes of these demographically based score differences and to identify potential mechanisms for avoiding future instances of discrepancy. In this study, we used a combination of statistical methods and human review to propose hypotheses about the root cause of score differences and whether such discrepancies reflect inadequacies of e-rater, human scoring, or both. The human rating process was found to be influenced strongly by the scale structure and did not fully correspond to the e-rater scoring mechanism. The human raters appeared to be using conditional logic and a rule-based approach to their scoring, while e-rater uses linear weighting of all the features. These analyses have implications for future research and operational policies for the scoring of the rGRE.