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ourse coherence, and many studies have targeted pronoun processing to examine gender consistency. When reflexive pronouns encounter gender mismatched typical gender role nouns, readers slow down their reading, and this mismatch effect were assigned to a conflict between the gender of the reflexive pronoun and the gender information associated with the typical gender role noun. Native speakers are able to quickly and accurately associate the reflexive expression with the antecedent to understand the meaning of the sentence. For native speakers, gender inconsistency may trigger a mismatch effect and increase the reading time.

Duffy & Keir (2004) examined native English speakers reading sentences through an eye-tracking experiment and found the reading time for the eye-tracking measure reflexive pronoun and its subsequent region increased significantly when the gender of the pronoun word did not match the stereotype of the role noun. Participants indicated the gender of the role noun by reading a target sentence where the antecedent was a role name with a gender stereotype, the role name was usually male or female, and the target pronoun was reflexive pronoun. 

Chapter Three Methodology………………….………..29

3.1 Research questions and hypotheses……..……………….29

3.2 General design………………….……….30

3.3 Research methods……………………………30

Chapter Four Results and Discussion………….…………39

4.1 Data analysis and results…………………….39

4.1.1 The antecedent region………………….………40

4.1.2 The reflexive region ………………………44

Chapter Five Conclusion…………………………60

5.1 Main findings of the research……………………………..60

5.2 Implications of the research……………………….61 

Chapter Four   Results and Discussion

4.1 Data analysis and results

The average comprehension accuracy of the current experiment was 84.4%, and the judgment accuracy of the participants was relatively high and correct. It shows that the participants read the sentences carefully with high reliability, and the data obtained are reliable. After the experiments were completed, the Data Viewer was used for data integration. Firstly, the obtained data were cleaned to remove data for fixation points less than 80ms or more than 1200ms, and to exclude the abnormal value that is more than 3 standard deviations of the average value of the participant, because fixation points with too long or too short eye movements do not reflect reading processing (Rayner, 1998). A total of 0.9% of the trials were excluded. Once the data were sorted out, a linear mixed-effects model was conducted using the lme4 package in R language software (version 4.0.2) (Baayen et al., 2008), with participants and items set as random factors. The data collection was based on sentences with fixation points, and high skimming rate may bring about a decrease in the reliability of the data collection, so to ensure the validity of the data, this study first divided the experimental sentences into six interest regions (See Table 4.1 for the specific division of interest regions). 

Chapter Five   Conclusion

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