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Doctoral Dissertation Research: The Role of Recommendation Letters in Selective College Admissions

Doctoral Dissertation Research: The Role of Recommendation Letters in Selective College Admissions
博士论文研究:推荐信在选择性大学招生中的作用
批准号:
1434723
负责人:
William Carbonaro
金额:
$1.2万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-09-01 至 2015-12-31

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中文摘要
翻译
本论文建立在关于学校影响,地位的实现,并通过检查在选择性大学招生教师推荐的作用分层的研究。通过有效维持不平等的过程,父母可能试图通过将子女送到资源充足的学校来确保他们的优势,这些学校被认为在学习和生活成果方面具有优势。 然而,根据学校效应研究,学校特征在学生成绩变化中所占的比例相对较小。使用混合方法的方法,本论文测试是否推荐信写的教师在资源丰富的学校提供了一个优势,在高选择性的大学录取相对于同样合格的申请人从较低的特权schoes.Letters的推荐被假定为提供一个优势,从特权高中的学生在选择性的大学admissions。这些信件是一种机制,通过这种机制,学校的特点直接影响大学录取的可能性,而不是由学生的成绩介导的。该项目为社会学研究引入了新的方法和数据:计算语言学分析,它位于计算机和社会科学的交叉点。关键概念和方法将以社会学家易于理解和有用的方式进行翻译和应用。该项目产生的数据最终将提供给其他学者,实质性的研究结果将与从业人员分享。与15-30名高度选择性的学院和大学的招生官员进行定性访谈,将确定教师评估在招生过程中的作用。该项目的核心是收集了近25,000份教师评价,这些评价已提交给一所顶级研究型大学,并与申请人的有限传记信息和成就指标相关联。这些信件的样本使用传统的定性方法进行分析,整个语料库将使用计算语言学分析进行定量检查。最后,一个实验将测试定性访谈的结果,并衡量与高中特征相关的推荐信的差异如何影响高选择性大学的录取决定。
英文摘要
This dissertation builds on research regarding school effects, status attainment, and stratification by examining the role of teacher recommendations in selective college admissions. Through the process of effectively maintained inequality, parents may attempt to secure advantages for their children by sending them to well-resourced schools that are believed to provide an advantage in learning and life-outcomes. According to school effects research, though, school characteristics account for a relatively small proportion of the variation in student outcomes. Using a mixed-methods approach, this dissertation tests whether letters of recommendation written by teachers at well-resourced schools provide an advantage in highly selective college admissions relative to equally qualified applicants from less privileged schools.Letters of recommendation are posited to provide an advantage to students from privileged high schools in selective college admissions. These letters are a mechanism through which school characteristics directly affect the likelihood of college admission that is not mediated by student achievement. This project introduces new methods and data to sociological inquiry: computational linguistic analysis, which lies at the intersection of computer and social sciences. Key concepts and methods will be translated and applied in a way that is accessible and useful to sociologists. Data generated by this project will eventually be made available to other scholars and substantive findings will be shared with practitioners.Qualitative interviews with 15-30 admissions officers at highly selective colleges and universities will establish the role of teacher evaluations in the admissions process. The core of the project is a collection of nearly 25,000 teacher evaluations that were submitted to a top research university which are linked to limited biographical information and achievement indicators of applicants. A sample of these letters is analyzed using traditional qualitative methods and the entire corpus will be quantitatively examined using computational linguistic analysis. Finally, an experiment will test the findings of the qualitative interviews and measure how differences in letters of recommendation associated with high school characteristics impact admissions decisions at highly selective universities.
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