It has been proposed that in online sentence comprehension the dependency between a reflexive pronoun such as himself/herself and its antecedent is resolved using exclusively syntactic constraints. Under this strictly syntactic search account, Principle A of the binding theory—which requires that the antecedent c-command the reflexive within the same clause that the reflexive occurs in—constrains the parser's search for an antecedent. The parser thus ignores candidate antecedents that might match agreement features of the reflexive (e.g., gender) but are ineligible as potential antecedents because they are in structurally illicit positions. An alternative possibility accords no special status to structural constraints: in addition to using Principle A, the parser also uses non-structural cues such as gender to access the antecedent. According to cue-based retrieval theories of memory (e.g., Lewis and Vasishth, ), the use of non-structural cues should result in increased retrieval times and occasional errors when candidates partially match the cues, even if the candidates are in structurally illicit positions. In this paper, we first show how the retrieval processes that underlie the reflexive binding are naturally realized in the Lewis and Vasishth () model. We present the predictions of the model under the assumption that both structural and non-structural cues are used during retrieval, and provide a critical analysis of previous empirical studies that failed to find evidence for the use of non-structural cues, suggesting that these failures may be Type II errors. We use this analysis and the results of further modeling to motivate a new empirical design that we use in an eye tracking study. The results of this study confirm the key predictions of the model concerning the use of non-structural cues, and are inconsistent with the strictly syntactic search account. These results present a challenge for theories advocating the infallibility of the human parser in the case of reflexive resolution, and provide support for the inclusion of agreement features such as gender in the set of retrieval cues.
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