民族志
前景化
社会学
叙述的
认识论
人类学
文学类
艺术
哲学
作者
Anthony Kwame Harrison
出处
期刊:Oxford University Press eBooks
[Oxford University Press]
日期:2018-05-24
被引量:22
标识
DOI:10.1093/oso/9780199371785.001.0001
摘要
Ethnography (Understanding Qualitative Research) provides a comprehensive guide to understanding, conceptualizing, and critically assessing ethnographic research and its resultant texts. Through a series of discussions and illustrations, utilizing both classic and contemporary examples, the book highlights distinct features of ethnography as both a research methodology and a writing tradition. It emphasizes the importance of training—including familiarity with culture as an anthropologically derived concept and critical awareness of the history of ethnography. To this end, it introduces the notion of ethnographic comportment, which serves as a standard for engaging and gauging ethnography. Indeed, ethnographic comportment issues from a familiarity with ethnography’s problematic past and inspires a disposition of accountability for one’s role in advancing ethnographic practices. Following an introductory chapter outlining the emergence and character of ethnography as a professionalized field, subsequent chapters conceptualize ethnographic research design, consider the practices of representing research methodologies, discuss the crafting of accurate and evocative ethnographic texts, and explain the different ways in which research and writing gets evaluated. While foregrounding interpretive and literary qualities that have gained prominence since the late twentieth century, the book properly situates ethnography at the nexus of the social sciences and the humanities. Ethnography (Understanding Qualitative Research) presents novice ethnographers with clear examples and illustrations of how to go about conducting, analyzing, and representing their research; its primary purpose, however, is to introduce readers to effective practices for understanding and evaluating the quality of ethnography.
科研通智能强力驱动
Strongly Powered by AbleSci AI