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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
本论文通过考察教师推荐在选择性大学招生中的作用,建立在关于学校效应、地位获得和分层的研究的基础上。通过有效地维持不平等的过程,父母可能会试图通过送孩子去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结果方面提供优势。然而,根据学校效应研究,学校特征在学生成绩差异中所占的比例相对较小。这篇论文使用混合方法,检验了资源充足的学校的老师写的推荐信在高选择性大学录取中是否比来自不那么优越的学校的同等资格的申请者具有优势。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,而不是通过学生的成绩来调节。这个项目为社会学研究引入了新的方法和数据:计算语言分析,它位于计算机和社会科学的交叉点。关键概念和方法将以一种社会学家可以理解和有用的方式进行翻译和应用。这个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实践者分享。对高度挑剔的学院和大学的15-30名招生官员进行的资格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提交给一所顶尖研究型大学的近25,000份教师评估,这些评估与申请者有限的传记信息和成就指标有关。这些信件的样本使用传统的定性方法进行分析,并将使用计算语言分析对整个语料库进行定量检查。最后,一项实验将检验定性面试的结果,并衡量与高中特点相关的推荐信的差异如何影响高选择性大学的招生决定。
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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