<?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>2026-09-20T15:07:34Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/68444" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/68444</identifier><datestamp>2022-01-13T07:54:44Z</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">Michael Flaxman.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Raford, Noah (Noah A.)</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Dept. of Urban Studies and Planning.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Urban Studies and Planning</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2012-01-12T19:28:14Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2012-01-12T19:28:14Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2011</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2011</dim:field>
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   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">769007259</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2011.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (p. 224-231).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">This dissertation explores the role that participatory online collective intelligence systems might play in urban planning research. Specifically, it examines methodological and practical issues raised by the design and use of such systems in long-term policy formulation, with a focus on their potential as data collection instruments and analytical platforms for qualitative scenario planning. The research questions addressed herein examine how the use of collective intelligence platforms informs the process of scenario planning in urban public policy. Specifically, how (if at all) does the design and deployment of such platforms influence the number and type of participants involved, people's reasons for participation, the kinds of activities they perform, and the speed and timeline of the scenario creation process? Finally, what methodological considerations does the use of such instruments raise for urban planning research in the future? In-depth interviews with experts in the fields of urban planning, public participation, crowdsourcing, and scenarios were conducted, combined with secondary analysis of comparable approaches in related fields. The results were used to create an analytical framework for comparing systems across a common set of measurement constructs. Findings were then used to develop a series of prototypical online platforms that generated data for two related urban planning cases. These were then analyzed relative to a base case, using the framework described above. The dissertation closes with a reflection on how the use of such online approaches might impact the role and process of qualitative scenario research in public policy formulation in the future, and what this suggests for subsequent scholarly inquiry.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Noah Raford.</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">231 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">Urban Studies and Planning.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Large scale participatory futures systems : a comparative study of online scenario planning approaches</dim:field>
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   	&lt;Title>Large scale participatory futures systems : a comparative study of online scenario planning approaches&lt;/Title>
   	&lt;Subtitle>Comparative study of online scenario planning approaches&lt;/Subtitle>
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   	&lt;PublicationDate>2011&lt;/PublicationDate>
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    &lt;Keyword>Urban Studies and Planning.&lt;/Keyword>
   	&lt;Abstract>This dissertation explores the role that participatory online collective intelligence systems might play in urban planning research. Specifically, it examines methodological and practical issues raised by the design and use of such systems in long-term policy formulation, with a focus on their potential as data collection instruments and analytical platforms for qualitative scenario planning. The research questions addressed herein examine how the use of collective intelligence platforms informs the process of scenario planning in urban public policy. Specifically, how (if at all) does the design and deployment of such platforms influence the number and type of participants involved, people&amp;apos;s reasons for participation, the kinds of activities they perform, and the speed and timeline of the scenario creation process? Finally, what methodological considerations does the use of such instruments raise for urban planning research in the future? In-depth interviews with experts in the fields of urban planning, public participation, crowdsourcing, and scenarios were conducted, combined with secondary analysis of comparable approaches in related fields. The results were used to create an analytical framework for comparing systems across a common set of measurement constructs. Findings were then used to develop a series of prototypical online platforms that generated data for two related urban planning cases. These were then analyzed relative to a base case, using the framework described above. The dissertation closes with a reflection on how the use of such online approaches might impact the role and process of qualitative scenario research in public policy formulation in the future, and what this suggests for subsequent scholarly inquiry.&lt;/Abstract>
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