A significant challenge in fitting metamodels of large-scale simulations with sufficient accuracy is in the computational time required for rigorous statistical validation. This paper addresses the statistical computation issues associated with the Bootstrap and modified PRESS statistic, which yield key metrics for error measurements in metamodelling validation. Experimentation is performed on different programming languages, namely, MATLAB, R, and Python, and implemented on different computing architectures including traditional multicore personal computers and high-power clusters with parallel computing capabilities. This study yields insight into the effect that programming languages and computing architecture have on the computational time for simulation metamodel validation. The experimentation is performed across two scenarios with varying complexity. 相似文献
This article examines the relationship between being a sexual woman and a good mother in The Simpsons, Family Guy, and South Park. Considering the sexual criticisms of women in the “Mommy Wars” which continue to be fought across the United States, we find that these three programs reproduce conservative assumptions about women's sexuality and motherhood. Through critical constructionist theories of humor and motherhood, mothers from each program are analyzed and the relationship between their sexuality and motherliness is examined in detail. We conclude with a discussion of the social constrictions of reality that humorous popular culture both exposes and reproduces. 相似文献
The authors take a critical language pedagogy approach to examining a 2011 controversy over disparaging comments towards Mexicans made by commentators of the British Broadcasting Corporation’s automotive show Top Gear. In particular, they focus on the characterization of groups and individuals according to their nationality and examine the ubiquity of nationalism and its ability to shape our conception of culture and in turn our understandings of others as members of ‘X national culture.’ The fact that humor is often a justification for national stereotyping and that these stereotypes are also connected to racist discourse are also explored. In the second part of the article, the implications of the stereotyping debate for language classrooms are considered. The authors argue that the controversy itself can be used as a tool for critical engagement that helps students deconstruct the underlying nationalist paradigm in L2 classrooms and build greater intercultural awareness.
Español: Los autores examinan, desde una perspectiva de la pedagogía crítica del lenguaje, la controversia que surgió en el 2011 debido a los comentarios nocivos hechos hacia los mexicanos por los locutores del show automotriz del BBC, Top Gear. En particular, se enfocan en la caracterización de los grupos e individuos de acuerdo a su nacionalidad, y examinan la ubiquidad del nacionalismo y su capacidad para darle forma a nuestra conceptualización de la cultura y, a su vez, nuestra forma de ver a otros como miembros de una ‘cultural nacional X’. Los autores también exploran el hecho de que a menudo se utiliza el humor como una justificación para los estereotipos nacionales, y que estos estereotipos también están conectados al discurso racista. En la segunda parte del artículo, se consideran las implicaciones para la enseñanza de idiomas del debate sobre los estereotipos. Argumentan los autores que la controversia en sí se puede utilizar como una herramienta para promover una postura crítica que ayude a los alumnos a deconstruir el paradigma subyacente del nacionalismo en el salón de lenguas extranjeras y fomente la conciencia intercultural. 相似文献
We present a study of the relationship between gender, linguistic style, and social networks, using a novel corpus of 14,000 Twitter users. Prior quantitative work on gender often treats this social variable as a female/male binary; we argue for a more nuanced approach. By clustering Twitter users, we find a natural decomposition of the dataset into various styles and topical interests. Many clusters have strong gender orientations, but their use of linguistic resources sometimes directly conflicts with the population‐level language statistics. We view these clusters as a more accurate reflection of the multifaceted nature of gendered language styles. Previous corpus‐based work has also had little to say about individuals whose linguistic styles defy population‐level gender patterns. To identify such individuals, we train a statistical classifier, and measure the classifier confidence for each individual in the dataset. Examining individuals whose language does not match the classifier's model for their gender, we find that they have social networks that include significantly fewer same‐gender social connections and that, in general, social network homophily is correlated with the use of same‐gender language markers. Pairing computational methods and social theory thus offers a new perspective on how gender emerges as individuals position themselves relative to audiences, topics, and mainstream gender norms. 相似文献