Focusing on African American novelist Gloria Naylor’s fiction Mama Day, this article intends to analyze Mama Day and George’s distinctive relationships with maternal spaces, particularly based on French philosopher ...Focusing on African American novelist Gloria Naylor’s fiction Mama Day, this article intends to analyze Mama Day and George’s distinctive relationships with maternal spaces, particularly based on French philosopher Luce Irigaray’s philosophy concerning maternal spaces and a feminine way of communication. It is to argue that the two characters’ different ways of communicating with the maternal spaces result in their different endings in the narrative, as well as their different degrees of healing, either healing their own wounded relationships with their mothers or healing the disconnection between men and women. This finding unravels Naylor’s implicit ethical and philosophical messages in writing George’s mystic and tragic death. In addition, by engaging Mama Day in active and feminine communication with maternal spaces, Naylor successfully re-establishes “the missing pillar” of the female ancestry that Irigaray observes on Western civilization, thus offering a possibility for a woman to construct her female subjectivity with reference to her maternal origin.展开更多
Ranking and rating individuals is a fundamental problem in multiple comparisons. One of the most well-known approaches is the Plackett-Luce model, in which the ordering is decided by the maximum likelihood estimator. ...Ranking and rating individuals is a fundamental problem in multiple comparisons. One of the most well-known approaches is the Plackett-Luce model, in which the ordering is decided by the maximum likelihood estimator. However, the maximum likelihood estimate(MLE) does not exist when some individuals are never ranked lower than others or lose all their races. In this note, we proposed a penalized likelihood method to address this problem. As the penalized parameter goes to zero, the penalized MLE converges to the original MLE. Further, there exists a critical point in which the penalized likelihood ranking is independent of the choice of the penalized parameter. Several numerical examples are provided.展开更多
文摘Focusing on African American novelist Gloria Naylor’s fiction Mama Day, this article intends to analyze Mama Day and George’s distinctive relationships with maternal spaces, particularly based on French philosopher Luce Irigaray’s philosophy concerning maternal spaces and a feminine way of communication. It is to argue that the two characters’ different ways of communicating with the maternal spaces result in their different endings in the narrative, as well as their different degrees of healing, either healing their own wounded relationships with their mothers or healing the disconnection between men and women. This finding unravels Naylor’s implicit ethical and philosophical messages in writing George’s mystic and tragic death. In addition, by engaging Mama Day in active and feminine communication with maternal spaces, Naylor successfully re-establishes “the missing pillar” of the female ancestry that Irigaray observes on Western civilization, thus offering a possibility for a woman to construct her female subjectivity with reference to her maternal origin.
基金partially supported by the Fundamental Research Funds for the Central Universities(South-Central University for Nationalities(CZQ19010))by National Natural Science Foundation of China(No.11801576)+1 种基金by the Scientific Research Funds of South-Central University For Nationalities(No.YZZ17007)partially supported by the National Natural Science Foundation of China(No.11871237)
文摘Ranking and rating individuals is a fundamental problem in multiple comparisons. One of the most well-known approaches is the Plackett-Luce model, in which the ordering is decided by the maximum likelihood estimator. However, the maximum likelihood estimate(MLE) does not exist when some individuals are never ranked lower than others or lose all their races. In this note, we proposed a penalized likelihood method to address this problem. As the penalized parameter goes to zero, the penalized MLE converges to the original MLE. Further, there exists a critical point in which the penalized likelihood ranking is independent of the choice of the penalized parameter. Several numerical examples are provided.
