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What Do Government And Nonprofit
Stakeholders Want To Know About Nuclear
Fuel Cycle? A Semantic Network Analysis
Approach
Nan Li
Dominique Brossard*
Dietram Scheufele
Department of Life Sciences Communication
College of Agricultural and Life Sciences
University of Wisconsin – Madison, USA
SRA Annual Meeting, Baltimore, MD
December 8-11 2013
NUCLEAR ENERGY IS MORE AND MORE POLITICIZED

Friedrichs, J. (2011). Peak energy and climate change: The double bind of post-normal science. Futures, 43(4), 469–
477. .
NUCLEAR FUEL CYCLES: COMPLEX RISKS AND
REGULATORY UNCERTAINTY
• Cost
- Capital cost, operating cost,
maintenance cost, carbon emission
credits

• Waste management
- Feasibility of geological disposal,
reprocessing and recycling

-

Safety
- Power plant safety, safety of the
overall fuel cycle

• Nuclear proliferation

MIT. (2003). The future of nuclear power (pp. 1–26). Cambridge, MA.
STAKEHOLDERS APPLY DIFFERENT MENTAL
MODELS WHEN MAKING DECISIONS

Skarlatidou, A., Cheng, T., & Haklay, M. (2012). What do lay people want to know about the disposal of nuclear waste?
A mental model approach to the design and development of an online risk communication. Risk Analysis, 32(9), 1496–
511.
OUR PROJECT
• Identify U.S. federal agencies and nonprofit organizations as
two important stakeholders involved in making policy decisions
• Understand and compare how they perceive the areas
associated with the risks of nuclear fuel cycle
• Apply a semantic network analysis approach to examining the
stakeholders’ mental models
METHODS
• Conduct one-hour-long cognitive interviews with 6 government and 6
nonprofit stakeholders between April and June 2012
• Ask questions about different dimensions of the risks associated with
nuclear fuel cycle (e.g., economics, safety, waste, proliferation etc.)
• Use the artificial neural network software CATPAC II to analyze the
transcripts (9,929 words for government and 12,130 words for nonprofit
stakeholders)
• Describe the contents of mental models using Hierarchical Cluster
Analysis (HCA) and Multidimensional Scaling (MDS)
HOW THE SOFTWARE WORKS
• Read through the text with a window of n (n=5) words (e.g., 1 to 6, 2
to 7, 3 to 8) and document the co-occurring patterns of words
• Hierarchical Cluster Analysis to analyze the word covariance matrix
- The clustered words represent the frequently co-occurring concepts

• Multidimensional Scaling analysis helps draw the “conceptual maps”
and visualize the contents of mental models
- The grouped words represent the emergent meaning and dominant themes of
the text
HCA RESULTS: GOVERNMENT STAKEHOLDERS
Yucca
Mountain

Environment, Transportation
and Local Impact

C1

C2

Recy
cling

C3

Prolifera
tion

C4

Economic and
Waste
Management

C5
MDS MAP: GOVERNMENT STAKEHOLDERS
Cluster 3: Economic and
waste management

Cluster 5:
Environment,
transportation and
local impact

Cluster 2:
Proliferation

Cluster 4:
Recycling
Notes: Dark points represent the concepts that do not fit the results of hierarchical cluster analysis
HCA RESULTS: NONPROFIT STAKEHOLDERS
Proliferation

C1

Alternativ
e energy

C2

Economi
c

C3

Yucca Mountain

Reproc
essing

C4

C5

Uranium
and waste
storage

C6
MDS MAP: NONPROFIT STAKEHOLDERS
Cluster 4:
Yucca
Mountain
Cluster 6: Uranium and
waste storage

Cluster 2: Alternative energy

Cluster 3: Economic

Cluster 1: Proliferation
Notes: Dark points represent the concepts that do not fit the results of hierarchical cluster analysis
SUMMARY
Government stakeholders

Nonprofit stakeholders

1. Yucca Mountain
Cluster 1a: administration, YuccaMountain,
Cluster 1b: backend, disposal, storage
Cluster 1c: different, important, reactor

1. Yucca Mountain
Cluster 4a: different, policy, disposal, longterm, repository,
spentfuel, YuccaMountain,
Cluster 4b: government, problem

2. Proliferation
Cluster 4: concern, fuelcycle, nuclear, proliferation, course,
reprocessing

2. Proliferation
Cluster 1a: amount, nonproliferation, United States, facility,
world
Cluster 1b: important, safety
Cluster 1c: plutonium, water, proliferation, weapon

3. Economic and waste management
3. Economic
Cluster 5: cost, fuel, facility, safety, technology, economic, waste, Cluster 3a: cost, country, people, reactor,
people, management, policy
Cluster 3b: economic, fuelcycle
4. Recycling
Cluster 3a: material, recycle,
Cluster 3b: operating, plant

4. Reprocessing
Cluster 5a: difficult, time
Cluster 5b: political, reprocessing, technology

5. Environment, transportation and local impact
Cluster 2a: benefit, transportation, state, time,
Cluster 2b: closedfuelcycle, energy, nuclearenergy, commission,
question, policymaker
Cluster 2c: certainly, environment, Fukushima
Cluster 2d: example, United States, nuclearpower, uranium

5. Alternative energy
Cluster 2a: energy, nuclearpower, state
Cluster 2b: gas, wind, plant, power
6. Uranium and waste storage
Cluster 6: fact, fuel, nuclear, year, uranium, storage, waste

Note: Bolded words are unique to the particular group in each column.
DISCUSSION AND CONCLUSION
• Mental models vary for different stakeholders because they are
closely related to institutional responsibilities and tasks
• Semantic network analysis approach is appropriate for describing
and comparing the contents of stakeholder mental models

• Should not assume the consistency in cognitions and risk-related
beliefs between stakeholders with distinct expertise and interests
• Risk communication efforts are needed to promote stakeholder
participation in policymaking
Thanks for your attention
dbrossard@wisc.edu
Twitter: @brossardd
This material is based on work supported by grants
from the U.S. Department of Energy (Contract No.
120341). Any opinions, findings, and conclusions or
recommendations expressed in this material are
those of the authors and do not necessarily reflect the
views of the Department of Energy.

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What do government and nonprofit stakeholders want to know about nuclear fuel cycles? A semantic analysis approach

  • 1. What Do Government And Nonprofit Stakeholders Want To Know About Nuclear Fuel Cycle? A Semantic Network Analysis Approach Nan Li Dominique Brossard* Dietram Scheufele Department of Life Sciences Communication College of Agricultural and Life Sciences University of Wisconsin – Madison, USA SRA Annual Meeting, Baltimore, MD December 8-11 2013
  • 2. NUCLEAR ENERGY IS MORE AND MORE POLITICIZED Friedrichs, J. (2011). Peak energy and climate change: The double bind of post-normal science. Futures, 43(4), 469– 477. .
  • 3. NUCLEAR FUEL CYCLES: COMPLEX RISKS AND REGULATORY UNCERTAINTY • Cost - Capital cost, operating cost, maintenance cost, carbon emission credits • Waste management - Feasibility of geological disposal, reprocessing and recycling - Safety - Power plant safety, safety of the overall fuel cycle • Nuclear proliferation MIT. (2003). The future of nuclear power (pp. 1–26). Cambridge, MA.
  • 4. STAKEHOLDERS APPLY DIFFERENT MENTAL MODELS WHEN MAKING DECISIONS Skarlatidou, A., Cheng, T., & Haklay, M. (2012). What do lay people want to know about the disposal of nuclear waste? A mental model approach to the design and development of an online risk communication. Risk Analysis, 32(9), 1496– 511.
  • 5. OUR PROJECT • Identify U.S. federal agencies and nonprofit organizations as two important stakeholders involved in making policy decisions • Understand and compare how they perceive the areas associated with the risks of nuclear fuel cycle • Apply a semantic network analysis approach to examining the stakeholders’ mental models
  • 6. METHODS • Conduct one-hour-long cognitive interviews with 6 government and 6 nonprofit stakeholders between April and June 2012 • Ask questions about different dimensions of the risks associated with nuclear fuel cycle (e.g., economics, safety, waste, proliferation etc.) • Use the artificial neural network software CATPAC II to analyze the transcripts (9,929 words for government and 12,130 words for nonprofit stakeholders) • Describe the contents of mental models using Hierarchical Cluster Analysis (HCA) and Multidimensional Scaling (MDS)
  • 7. HOW THE SOFTWARE WORKS • Read through the text with a window of n (n=5) words (e.g., 1 to 6, 2 to 7, 3 to 8) and document the co-occurring patterns of words • Hierarchical Cluster Analysis to analyze the word covariance matrix - The clustered words represent the frequently co-occurring concepts • Multidimensional Scaling analysis helps draw the “conceptual maps” and visualize the contents of mental models - The grouped words represent the emergent meaning and dominant themes of the text
  • 8. HCA RESULTS: GOVERNMENT STAKEHOLDERS Yucca Mountain Environment, Transportation and Local Impact C1 C2 Recy cling C3 Prolifera tion C4 Economic and Waste Management C5
  • 9. MDS MAP: GOVERNMENT STAKEHOLDERS Cluster 3: Economic and waste management Cluster 5: Environment, transportation and local impact Cluster 2: Proliferation Cluster 4: Recycling Notes: Dark points represent the concepts that do not fit the results of hierarchical cluster analysis
  • 10. HCA RESULTS: NONPROFIT STAKEHOLDERS Proliferation C1 Alternativ e energy C2 Economi c C3 Yucca Mountain Reproc essing C4 C5 Uranium and waste storage C6
  • 11. MDS MAP: NONPROFIT STAKEHOLDERS Cluster 4: Yucca Mountain Cluster 6: Uranium and waste storage Cluster 2: Alternative energy Cluster 3: Economic Cluster 1: Proliferation Notes: Dark points represent the concepts that do not fit the results of hierarchical cluster analysis
  • 12. SUMMARY Government stakeholders Nonprofit stakeholders 1. Yucca Mountain Cluster 1a: administration, YuccaMountain, Cluster 1b: backend, disposal, storage Cluster 1c: different, important, reactor 1. Yucca Mountain Cluster 4a: different, policy, disposal, longterm, repository, spentfuel, YuccaMountain, Cluster 4b: government, problem 2. Proliferation Cluster 4: concern, fuelcycle, nuclear, proliferation, course, reprocessing 2. Proliferation Cluster 1a: amount, nonproliferation, United States, facility, world Cluster 1b: important, safety Cluster 1c: plutonium, water, proliferation, weapon 3. Economic and waste management 3. Economic Cluster 5: cost, fuel, facility, safety, technology, economic, waste, Cluster 3a: cost, country, people, reactor, people, management, policy Cluster 3b: economic, fuelcycle 4. Recycling Cluster 3a: material, recycle, Cluster 3b: operating, plant 4. Reprocessing Cluster 5a: difficult, time Cluster 5b: political, reprocessing, technology 5. Environment, transportation and local impact Cluster 2a: benefit, transportation, state, time, Cluster 2b: closedfuelcycle, energy, nuclearenergy, commission, question, policymaker Cluster 2c: certainly, environment, Fukushima Cluster 2d: example, United States, nuclearpower, uranium 5. Alternative energy Cluster 2a: energy, nuclearpower, state Cluster 2b: gas, wind, plant, power 6. Uranium and waste storage Cluster 6: fact, fuel, nuclear, year, uranium, storage, waste Note: Bolded words are unique to the particular group in each column.
  • 13. DISCUSSION AND CONCLUSION • Mental models vary for different stakeholders because they are closely related to institutional responsibilities and tasks • Semantic network analysis approach is appropriate for describing and comparing the contents of stakeholder mental models • Should not assume the consistency in cognitions and risk-related beliefs between stakeholders with distinct expertise and interests • Risk communication efforts are needed to promote stakeholder participation in policymaking
  • 14. Thanks for your attention dbrossard@wisc.edu Twitter: @brossardd This material is based on work supported by grants from the U.S. Department of Energy (Contract No. 120341). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the Department of Energy.

Editor's Notes

  1. - [INTRODUCTION]
  2. Nuclear energy is important to the future energy program for many countries.Nuclear energy is not normal scientific issue, because “facts are uncertain, values in dispute, stakes high and decisions urgent”It is important to integrate stakeholder concerns and other human factors into the risk management of nuclear energy
  3. The choice of nuclear fuel cycle is critical to the development of nuclear energy.Nuclear fuel cycle can be defined as a set of processes to make use of nuclear materials and to return it to normal state.[GRAPH]It starts with the mining the uranium ores and ends with the disposal of spent fuel in the nature.The U.S. has invested considerable R&D efforts in evaluating different nuclear fuel cycle options.The goal of the U.S. Department of Energy is to develop sustainable nuclear fuel cycle to inform future decisions.However, the regulation and management of nuclear fuel cycle faces a lot of uncertainty.For example, the U.S. has reached a stalemate regarding the management of the back-end of nuclear fuel cycle.The Yucca Mountain project was withdrawn and the government needs to figure out an optimal way to dispose nuclear waste.[TEXT]Also, the nuclear fuel cycle presents complex risks at different stages. For example, significant risks are associated with cost, waste management, safety, and nuclear proliferation.For each area, there are extensive concrete factors to take into account when assessing the risk. [READ THE TEXTS IF HAVING TIME]
  4. When assessing the risks associated with the back-end of nuclear fuel cycle, stakeholders tend to generate different mental representations of the problem to make decisions.To effectively integrate the concerns of the key stakeholders into risk management, it’s important to understand how they think about the issue at the first place. The mental model approach can be applied to examining the stakeholders’ cognitions and beliefs. [CLICK AND SHOW] The example here is an influence diagram showing what experts and the lay people want to know about nuclear waste.As we can tell from the diagram, while the lay people merely focus on the safety and transportation issues, the experts have much broader concerns on such areas as site selection, disposal and storage.While the approach has been used to identify the knowledge gap and misconception for the lay people, there are very few studies on comparing experts’ mental models. Our study attempts to fill the gap in literature.
  5. [CLICK AND READ]The goal of our study is three-foldFirst, we identify the U.S. federal agencies, such as Department of Energy and the Blue Ribbon Commission on America’s Nuclear Future, which was established in 2010 to review the policies on the back-end of nuclear fuel cycle, and other prominent nonprofit organizations and think tanks as important stakeholders involved in making policy decisions on nuclear fuel cycle. The nonprofit stakeholders were studied because of their active role in bridging the policymaking community and the general public. Also, these two groups often work together to make collective decisions on nuclear fuel cycle.Based on our analysis of the witnesses and attendees of the congressional hearings related nuclear energy, around 21% of them are affiliated with nonprofit sectors. [CLICK AND READ]So we want to understand and compare how each of the group perceives and understand the areas that are associated with the risks of nuclear fuel cycle.It’ll be interesting to see if they apply essentially different definitions to the problem or focus on different areas when evaluating the fuel cycle risks.[CLICK AND READ]In terms of method, a semantic network analysis was conducted. Previously many approaches were used to examine and visualize the contents of mental models, such as the influence diagram and the conceptual maps. The semantic network analysis was based on cognitive psychology, and it allows us to describe stakeholders’ mental models through an analysis of the structure of their language.The semantic network of the frequently mentioned concepts will be drawn and we can make inferences about the salient concerns in their mind, and how the top concerns link with each other.
  6. [CLICK AND SHOW]We conduct one-hour-long interviews with 6 government and 6 nonprofit stakeholders in 2012, each lasting about one hour on average. The interviewees are identified through content analyses of public meeting records. In order to reach sufficient number of people, we also did snowball sampling. We initially contacted the interviewees via phone and email and then get the interviews done over phone only. [CLICK AND SHOW]The interview questions are about different dimensions of the risks associated with nuclear fuel cycle, including economics, waste management, sustainability and proliferation.We also ask open questions to let the interviewees freely talk about the areas they could think of the fuel cycle risks. [CLICK AND SHOW]We use the artificial neutral network software CATPAC to analyze the 43 pages, single-spaced transcripts.The software provides two formats to describe the contents of mental models, including hierarchical cluster analysis and multidimensional scaling.The two analyses offer different perspectives to capture the same data and we are able to map out the top concerns in stakeholders’ minds.
  7. [CLICK AND SHOW]The software reads through the text with a window of five words.When a particular word appears in the window, the neuron is activated and remain activated as the word stays in the window.When two words appear in the same window, the software documents the correlation between the words in a covariance matrix [CLICK AND SHOW]A hierarchical cluster analysis is conducted to identify the word clusters, which represent the frequently co-occurring concepts[CLICK AND SHOW]Based on the same set of key words, a multidimensional scaling analysis helps show the network structure of the connected conceptsA mental mental could be visualized in a 2D representation of the multidimensional scaling analysisThe grouped words in the map represent the emergent meaning and the dominant themes of the text
  8. Here is the results of the hierarchical cluster analysis for the government stakeholders.Five clusters are identified for the government stakeholders[CLICK AND SHOW] cluster 1 is labeled Yucca Mountain, including concepts related to the debates on the Yucca Mountain project, such as disposal, storage, backend. [CLICK AND SHOW] cluster 2 is labeled environment, transportation and local impact, including such concepts as transportation, state, environment, Fukushima and policymaker[CLICK AND SHOW] cluster 3 is labeled recycling, focusing on concerns related to recycling of nuclear material[CLICK AND SHOW] cluster 4 is labeled proliferation, including the word reprocessing, which indicates the inherent mental connection between the two issues.[CLICK AND SHOW] cluster 5 is labeled economic and waste management, which represents mixed concerns on the economics of nuclear fuel cycle, safety and waste management issues.
  9. The figure shows the results of the multidimensional scaling. As it shows, we can visualize how the top concepts mentioned by interviewees are grouped on a 2D map.[CLICK TO SHOW ALL CLUSTER LABELS]The clusters identified in the hierarchical cluster analysis correlates with the grouped words in the map.However, concepts in cluster 1 (Yucca Mountain), as shown by the dark points, are adjacent to those in cluster 5 and cluster 4, which indicates the close relationships among these concepts. For example, the concepts “different” “storage” and “disposal” were included in cluster 5, which is about the environment, transportation and local impact. To be sure, the storage and disposal of nuclear waste are closely related to how the nuclear fuel cycle will impact the natural environment. However, it should be pointed out that the concepts hierarchically clustered might co-occur in the third or more dimensions that are not pictured on the 2D map.
  10. This figure shows the results of hierarchical cluster analysis for the nonprofit stakeholders. Six clusters are identified for the government stakeholders[CLICK AND SHOW] cluster 1 is labeled proliferation, including concepts related to proliferation and international security [CLICK AND SHOW] cluster 2 is labeled alternative energy, making comparisons between nuclear and other alternative sources of energy, such as gas and wind[CLICK AND SHOW] cluster 3 is labeled economic, representing concerns on costs and economical issue[CLICK AND SHOW] cluster 4 is labeled Yucca Mountain, differing from their governmental counterparts, the nonprofit stakeholders associated the project with “government” and “problem”[CLICK AND SHOW] cluster 5 is labeled reprocessing, indicating concerns on the political aspect of reprocessing process[CLICK AND SHOW] cluster 6 is labeled uranium and waste storage, which represents mixed concerns on availability of uranium and the long-term storage of waste.
  11. Similarly, this map shows the results of the multidimensional scaling analysis for the nonprofit stakeholders.[CLICK TO SHOW ALL CLUSTER LABELS]As with the government stakeholders, the clusters identified in the hierarchical cluster analysis correlates with the grouped words in the map for the nonprofit stakeholders.However, concepts in cluster 5 (reprocessing), as shown by the dark points, are adjacent to those in cluster 1 (proliferation), which is not surprising given the close relationship between the two issues.
  12. The table shows the areas of concerns and unique words for each group.The bolded words are unique to the group for each column. Although the two groups have common concerns on such issues as Yucca Mountain, proliferation, and economics, their focuses are different. For example, when discussing the Yucca Mountain project, the nonprofit stakeholders have concerned more about the problem of it, whereas the government ones think it’s important and do not associate it with any negative image. [CLICK AND SHOW] Moreover, while government stakeholders are concerned about recycling, their nonprofit counterparts focus more on the reprocessing process.While government stakeholders emphasize the transportation issue and the disastrous consequences of nuclear accident, the nonprofit ones did not assign priority to these issues.Instead, nonprofit stakeholders think of the nuclear fuel cycle in the context of clean energy development
  13. [CLICK AND READ]To explain the differences in expert mental models, we argue that the mental cognitions and risk beliefs are related to institutional responsibilities and tasks. For example, the majority of our government interviewees were staff members and commissioners of the Blue Ribbon Commission on America’s Nuclear Future. They have initial interests in examining the back-end of nuclear fuel cycle and have special committee on transportation and waste disposal. On the other hand, the nonprofit interviewees have interests in reaching out the general public, and hence integrate some popular discourseon clean energy development into their risk perception[CLICK AND READ]The semantic network analysis approach is previously identified as an appropriate method to describe the contents of mental models. Compared to other visualization technique to studying the mental models, the uses of CATPAC software allows us to limit the subjectivity in drawing the conceptual maps.[CLICK AND READ] Riskmanagersandregulatorsshouldnotassumetheconsistencyinthecognitionsandrisk-relatedbeliefsbetweendifferentstakeholders. Because of their conflicting interests and different expertise, the two groups of stakeholders here tend to define the risks associated with nuclear fuel cycle in different terms. [CLICK AND READ]Risk managers and regulators needtodevelopeffectiveriskcommunicationstrategiestocreatecommongroundandpromotethestakeholderparticipation
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