<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-20T06:47:28Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/45947" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/45947</identifier><datestamp>2022-01-13T07:54:48Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131022</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Arnold I. Barnett.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Chandler, Lincoln J., 1977-</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Operations Research Center.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Operations Research Center</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Sloan School of Management</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2009-06-30T16:46:11Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2009-06-30T16:46:11Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2008</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2008</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/45947</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">321054581</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2008.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (p. 189-192).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">For many decades, the American educational system has yielded significant differences in achievement among students in different racial groups, a phenomenon commonly known as the "Achievement Gap". Despite the volume of research devoted to studying achievement gaps, school administrators faced with the challenge of reducing these gaps have had limited success. There are a number of factors, regarding the individual, the school, and the setting, which can contribute to achievement gaps, but in a particular community, the prevalence of such factors, and their individual contribution to the gap, is unclear. In this dissertation, we employ a variety of statistical methods that provide a bridge between large-scale studies of achievement gaps and the analyses necessary to address the needs of a single community. First, we establish a collection of metrics designed to measure relative and absolute differences in achievement, for groups of arbitrary size and distribution. Using data from a middle-class, racially integrated school district, we employ these metrics to measure the magnitude of the achievement gap for individual students from grades three through eight. We also assess the potential role of previously-identified correlates of low achievement, such as poverty and student mobility. Last, we evaluate the potential impact of strategies for narrowing the gap.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Lincoln Jamond Chandler.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">Ph.D.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">192 p.</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">M.I.T. theses are protected by 
copyright. They may be viewed from this source for any purpose, but 
reproduction or distribution in any format is prohibited without written 
permission. See provided URL for inquiries about permission.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Operations Research Center.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">The minority achievement gap in a suburban school district</dim:field>
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   	&lt;Title>The minority achievement gap in a suburban school district&lt;/Title>
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   	&lt;PublicationDate>2008&lt;/PublicationDate>
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        	&lt;DisplayName>Chandler, Lincoln J., 1977-&lt;/DisplayName>
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   	&lt;Abstract>For many decades, the American educational system has yielded significant differences in achievement among students in different racial groups, a phenomenon commonly known as the &amp;quot;Achievement Gap&amp;quot;. Despite the volume of research devoted to studying achievement gaps, school administrators faced with the challenge of reducing these gaps have had limited success. There are a number of factors, regarding the individual, the school, and the setting, which can contribute to achievement gaps, but in a particular community, the prevalence of such factors, and their individual contribution to the gap, is unclear. In this dissertation, we employ a variety of statistical methods that provide a bridge between large-scale studies of achievement gaps and the analyses necessary to address the needs of a single community. First, we establish a collection of metrics designed to measure relative and absolute differences in achievement, for groups of arbitrary size and distribution. Using data from a middle-class, racially integrated school district, we employ these metrics to measure the magnitude of the achievement gap for individual students from grades three through eight. We also assess the potential role of previously-identified correlates of low achievement, such as poverty and student mobility. Last, we evaluate the potential impact of strategies for narrowing the gap.&lt;/Abstract>
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