{"id":{"repo_id":"montana-tech","oai_identifier":"oai:scholarworks.umt.edu:etd-1437"},"canonical_url":"https://search.dev.ndltd.org/etd/montana-tech/oai:scholarworks.umt.edu:etd-1437","repository":{"repo_id":"montana-tech","name":"Montana Technology","base_url":"https://scholarworks.umt.edu/do/oai/"},"display":{"title":"Exploring Public Participation Decision-making at Superfund Sites: A Mental Models Approach","abstract":"<p>While public policies and programs in the United States encourage public participation in agency decisions on environmental issues, how best to engage the public remains controversial. Public participation is more challenging when complex and uncertain scientific or technical issues are involved. This research applies a mental model methodology to explore what people engaged in Superfund site cleanup decisions think about when making public participation decisions. The intent is to find better ways of engaging people in constructive processes that achieve mutual understanding and lead to better decisions.</p> <p>An initial expert-informed mental model of public participation decision-making is developed based on a literature review, expert interviews, and professional workshop discussions. The model provides an illustrative framework of interconnected variables that is coherent to public participation professionals and consistent with current public participation theory. The \"expert\" model is used to guide semi-structured interviews of participants engaged in public participation at two Superfund sites. Transcribed interviews are analyzed using an iterative coding process to develop a participant mental model of public participation decision-making. Coding patterns are used to distinguish three characteristic ways of thinking - experiential, analytical, and strategic - which are associated with ad hoc, informing, and intentional types of public participation decision-making, respectively. Also, differences in expert and participant models indicate that experts are generally more attentive to broad-reaching, long-term societal objectives than participants.</p> <p>While established in risk communication research, this is the first known application of the Mental Models methodology for public participation research. The mental models that emerge from this research identify the diverse range of variables and the relationships among variables that should be considered during public participation planning and decision-making. The identified different ways of thinking about public participation reveal communication barriers that can lead to different decisions about how best to conduct public participation and frustrate efforts to work together. The implications of these findings to public participation theory, research, policy, and practice are discussed.</p>","abstract_html":"&lt;p&gt;While public policies and programs in the United States encourage public participation in agency decisions on environmental issues, how best to engage the public remains controversial. Public participation is more challenging when complex and uncertain scientific or technical issues are involved. This research applies a mental model methodology to explore what people engaged in Superfund site cleanup decisions think about when making public participation decisions. The intent is to find better ways of engaging people in constructive processes that achieve mutual understanding and lead to better decisions.&lt;/p&gt; &lt;p&gt;An initial expert-informed mental model of public participation decision-making is developed based on a literature review, expert interviews, and professional workshop discussions. The model provides an illustrative framework of interconnected variables that is coherent to public participation professionals and consistent with current public participation theory. The &quot;expert&quot; model is used to guide semi-structured interviews of participants engaged in public participation at two Superfund sites. Transcribed interviews are analyzed using an iterative coding process to develop a participant mental model of public participation decision-making. Coding patterns are used to distinguish three characteristic ways of thinking - experiential, analytical, and strategic - which are associated with ad hoc, informing, and intentional types of public participation decision-making, respectively. Also, differences in expert and participant models indicate that experts are generally more attentive to broad-reaching, long-term societal objectives than participants.&lt;/p&gt; &lt;p&gt;While established in risk communication research, this is the first known application of the Mental Models methodology for public participation research. The mental models that emerge from this research identify the diverse range of variables and the relationships among variables that should be considered during public participation planning and decision-making. The identified different ways of thinking about public participation reveal communication barriers that can lead to different decisions about how best to conduct public participation and frustrate efforts to work together. The implications of these findings to public participation theory, research, policy, and practice are discussed.&lt;/p&gt;","abstract_has_math":false,"creators":["Ackerlund, Walter Steven"],"institution":"University of Montana","degree_name":"Doctor of Philosophy (PhD)","degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-01-01T08:00:00Z","date_published":"2011-01-01T08:00:00Z","updated_at":"2026-07-24T03:13:21Z","subjects":["decision-making","mental models","public participation","conflict management","Superfund"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarworks.umt.edu/etd/418","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Ackerlund, Walter Steven"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:publisher","label":"Institution","values":["University of Montana"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["decision-making","mental models","public participation","conflict management","Superfund"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarworks.umt.edu/etd/418"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["<p>While public policies and programs in the United States encourage public participation in agency decisions on environmental issues, how best to engage the public remains controversial. Public participation is more challenging when complex and uncertain scientific or technical issues are involved. This research applies a mental model methodology to explore what people engaged in Superfund site cleanup decisions think about when making public participation decisions. The intent is to find better ways of engaging people in constructive processes that achieve mutual understanding and lead to better decisions.</p> <p>An initial expert-informed mental model of public participation decision-making is developed based on a literature review, expert interviews, and professional workshop discussions. The model provides an illustrative framework of interconnected variables that is coherent to public participation professionals and consistent with current public participation theory. The \"expert\" model is used to guide semi-structured interviews of participants engaged in public participation at two Superfund sites. Transcribed interviews are analyzed using an iterative coding process to develop a participant mental model of public participation decision-making. Coding patterns are used to distinguish three characteristic ways of thinking - experiential, analytical, and strategic - which are associated with ad hoc, informing, and intentional types of public participation decision-making, respectively. Also, differences in expert and participant models indicate that experts are generally more attentive to broad-reaching, long-term societal objectives than participants.</p> <p>While established in risk communication research, this is the first known application of the Mental Models methodology for public participation research. The mental models that emerge from this research identify the diverse range of variables and the relationships among variables that should be considered during public participation planning and decision-making. The identified different ways of thinking about public participation reveal communication barriers that can lead to different decisions about how best to conduct public participation and frustrate efforts to work together. The implications of these findings to public participation theory, research, policy, and practice are discussed.</p>"]},{"key":"dc:title","label":"Title","values":["Exploring Public Participation Decision-making at Superfund Sites: A Mental Models Approach"]}]}],"canonical_facts":{"dc:creator":["Ackerlund, Walter Steven"],"dc:description.abstract":["<p>While public policies and programs in the United States encourage public participation in agency decisions on environmental issues, how best to engage the public remains controversial. Public participation is more challenging when complex and uncertain scientific or technical issues are involved. This research applies a mental model methodology to explore what people engaged in Superfund site cleanup decisions think about when making public participation decisions. The intent is to find better ways of engaging people in constructive processes that achieve mutual understanding and lead to better decisions.</p> <p>An initial expert-informed mental model of public participation decision-making is developed based on a literature review, expert interviews, and professional workshop discussions. The model provides an illustrative framework of interconnected variables that is coherent to public participation professionals and consistent with current public participation theory. The \"expert\" model is used to guide semi-structured interviews of participants engaged in public participation at two Superfund sites. Transcribed interviews are analyzed using an iterative coding process to develop a participant mental model of public participation decision-making. Coding patterns are used to distinguish three characteristic ways of thinking - experiential, analytical, and strategic - which are associated with ad hoc, informing, and intentional types of public participation decision-making, respectively. Also, differences in expert and participant models indicate that experts are generally more attentive to broad-reaching, long-term societal objectives than participants.</p> <p>While established in risk communication research, this is the first known application of the Mental Models methodology for public participation research. The mental models that emerge from this research identify the diverse range of variables and the relationships among variables that should be considered during public participation planning and decision-making. The identified different ways of thinking about public participation reveal communication barriers that can lead to different decisions about how best to conduct public participation and frustrate efforts to work together. The implications of these findings to public participation theory, research, policy, and practice are discussed.</p>"],"dc:identifier":["https://scholarworks.umt.edu/etd/418"],"dc:publisher":["University of Montana"],"dc:subject":["decision-making","mental models","public participation","conflict management","Superfund"],"dc:title":["Exploring Public Participation Decision-making at Superfund Sites: A Mental Models Approach"],"dc:type":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T03:13:21Z"}