Everybody does it. It's like I've grown up on it. It's like how you felt about stuff when you were growing up.-Sam am, a 14-year-old girl, was one of seven participants in this study of young people's uses of Instant Messaging (IM). We want to take a moment to consider Sam's comment as a way of providing a conceptual framework for this study. To Sam, IM did not feel like technology, a term associated in many people's minds with objects that are complicated and difficult to understand or operate. When technology becomes "normal" in this way, it is no longer complicated, nor is it notable to its users. It is a fact of life, a way of being in the world, a producer of social subjects that find it unremarkable-so unremarkable that it seems "everybody does it." The social subject that develops in relation to this invisible technology is one who expects access, expects to be connected to friends at the stroke of a key, and expects to read and write in particular ways that lead to fulfilling connections with those friends. As Bourdieu (1997) put it, "The experience of a world that is 'taken for granted' presupposes agreement between the dispositions of the agents and the expectations or demands immanent in the world into which they are inserted" (p. 147).Sam's dispositions and the expectations placed upon her were in agreement. But it is important to note that these expectations did not emanate from her world at home. We suspect that because of Sam's assumption that "everybody does it," readers are imagining Sam to be middle class with economic resources that would locate her on the advantaged side of the digital divide. This was not the case. Sam happened to live in a community that had very inexpensive, municipally owned cable access, making home Internet access possible across class lines. Sam's parents 470 471 THIS STUDY examined the functions of Instant Messaging (IM) among seven youths who regularly used this digital technology in their daily lives. Grounded in theories of literacy as a social and semiotic practice, this research asked what functions IM served in participants' lives and how their social identities shaped and were shaped by this form of digital literacy. To answer these questions, we conducted interviews and videotaped IM sessions, adapting a verbal reporting procedure to document the IM strategies used. Data analysis involved using qualitative coding procedures informed by grounded theory (Strauss, 1987;Strauss & Corbin, 1990), which led to three patterns related to the functions of IM: language use, social networks, and surveillance. On the level of language use, participants manipulated the tone, voice, word choice, and subject matter of their messages to fit their communication needs, negotiating multiple narratives in the process. On the level of social networks, they designed their practice to enhance social relationships and statuses across contexts. And on the level of surveillance, they circulated texts across buddies, combated unwanted messages, assumed alternative identities, and overcame...

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In this article, I argue that the most common use of reader-response theory in the classroom is misguided in its emphasis on personal response and identification. After reconsidering the meaning of the "aesthetic stance" as defined in the work of Louise Rosenblatt, I discuss the social and political nature of readers, texts, and contexts. I include two examples of teachers talking about a work of children's literature to illustrate that when a text is about characters whose cultures and life worlds are very different from the reader's, disrupting the reader's inclination to identify with the text can heighten the reader's self consciousness and text consciousness. This stance should not be viewed as less aesthetic than a more direct or immediate relationship between reader and text. Finally, I argue for a broader view of what aesthetic reading can mean, one that addresses the social and political dimensions of texts and invites students to take pleasure in both the personal and the critical.

Abstract-While many bug prediction algorithms have been developed by academia, they're often only tested and verified in the lab using automated means. We do not have a strong idea about whether such algorithms are useful to guide human developers. We deployed a bug prediction algorithm across Google, and found no identifiable change in developer behavior. Using our experience, we provide several characteristics that bug prediction algorithms need to meet in order to be accepted by human developers and truly change how developers evaluate their code.

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