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Full-Text Articles in Social and Behavioral Sciences

The Surface Chemistry And Binding Interactions Of Lignin With Polymer-Encapsulated Gold Nanoparticles Acting As Model Microplastics, Oluwaseun Ayodeji Akinsola Jan 2024

The Surface Chemistry And Binding Interactions Of Lignin With Polymer-Encapsulated Gold Nanoparticles Acting As Model Microplastics, Oluwaseun Ayodeji Akinsola

All Master's Theses

This study investigates the surface chemistry and molecular-level interactions between lignin, a special type of natural organic matter, and polymer-capped gold nanoparticles, shedding light on the strength of adsorption between lignin and nanoscale polymer surfaces. Specifically, the study presents a variety of nanoscale polymer surfaces displaying different charged functional groups, using layer-by-layer assembly of three polyelectrolytes (polyallylamine hydrochloride (PAH)), polyacrylic acid (PAA), and poly(diallyldimethylammonium chloride (PDADMAC)) on 90 nm citrate-stabilized gold nanoparticles (AuNPs). This approach provides a library of polymer-encapsulated AuNPs for investigating the binding interactions of lignin to nanoscale polymers via spectroscopic techniques. ζ-potential, dynamic light scattering (DLS), …


Understanding The Impact Of Environmental Impact Assessment Research On Policy And Practice, Angus Morrison-Saunders, Annette Nykiel, Nicole Atkins Jan 2024

Understanding The Impact Of Environmental Impact Assessment Research On Policy And Practice, Angus Morrison-Saunders, Annette Nykiel, Nicole Atkins

Research outputs 2022 to 2026

There is an enormous and ever-growing body of environmental impact assessment (EIA) research, much of which is grounded in practice or seeks to advance it. In this paper we show how the impact of EIA research on policy and practice might be conceptualised and how to set about evidencing it. A framework is developed through literature review to account for impact in four areas pertaining to instrumental impact, conceptual impact, capacity building and knowledge brokerage and co-production. Methods for implementing the framework include citations within policy documents along with content analysis to determine influence and interviews or surveys with policy …


New Record Of Leucistic Blue Catfish, Ictalurus Furcatus (Siluriformes: Ictaluridae) From The Black River, Lawrence County, Arkansas, C.T. Mcallister, H.W. Robison Jan 2024

New Record Of Leucistic Blue Catfish, Ictalurus Furcatus (Siluriformes: Ictaluridae) From The Black River, Lawrence County, Arkansas, C.T. Mcallister, H.W. Robison

Journal of the Arkansas Academy of Science

The Blue Catfish, Ictalurus furcatus (Lesueur), the largest North American ictalurid, inhabits deep watersheds, impoundments, and main channels and backwaters of medium to large rivers, over mud, sand, and gravelly substrate. Its native range includes the Mississippi River basin from western Pennsylvania to southern South Dakota and southwestern Nebraska south to the Gulf of Mexico and in Alabama, Florida, The Rio Grande drainage of Texas and New Mexico (Page and Burr 2011). In Arkansas, I. furcatus is found throughout the Arkansas, Red, and Mississippi river drainages and has been stocked by the Arkansas Game and Fish Commission into reservoirs throughout …


Late Holocene Fire History Reconstruction Of Beaver Lake In The Northwest Lowlands Of The Olympic Peninsula, Grace Mckenney Jan 2024

Late Holocene Fire History Reconstruction Of Beaver Lake In The Northwest Lowlands Of The Olympic Peninsula, Grace Mckenney

All Master's Theses

Fire is an essential component of the landscapes and forests of the Pacific Northwest, including the temperate rainforests of the Olympic Peninsula. Previous fire history reconstructions from the peninsula show that fire return intervals varied throughout the postglacial period, primarily in response to climatic changes and corresponding shifts in vegetation. However, much less is known about the fire history of the low-elevation forests of the Olympic Peninsula and the role of cultural fire regimes in these environments. The purpose of this study was to reconstruct the paleoenvironmental history of a low-elevation study site, Beaver Lake, located in the northwestern part …


The Impact Of U.S. News And World Report College Rankings On Prospective Students’ Decisions And Enrollment Outcomes, Camilla Schneider Jan 2024

The Impact Of U.S. News And World Report College Rankings On Prospective Students’ Decisions And Enrollment Outcomes, Camilla Schneider

Honors Theses

The following paper further expands on previous research using more recent data which is important given changes in the last decade. This paper will answer the question: How do U.S. News and World Report college rankings impact college application and enrollment decisions for prospective students within American public and private colleges and universities? Application decisions refer to the choice to apply to a school while enrollment decisions refer to the choice to attend a school after being accepted. This paper analyzes Integrated Postsecondary Education Data System (IPEDs) admissions/applicant, fall enrollment, and financial data alongside historical USNWR rankings lists to investigate …


Does Innovation Facilitate Meeting The Co2 Emission Reduction Targets Of China: A Non-Linear Approach, Yifan Wang, Nadia Doytch, Mohammed Elheddad, Wei Li, Mengna Chi Jan 2024

Does Innovation Facilitate Meeting The Co2 Emission Reduction Targets Of China: A Non-Linear Approach, Yifan Wang, Nadia Doytch, Mohammed Elheddad, Wei Li, Mengna Chi

Ateneo School of Government Publications

China has been implementing energy efficiency and CO2 emission reduction schemes at the provincial level that have been embedded in the National Five Year Plans of the country. We set out to investigate the relationship between R&D expenditures and CO2 emissions in China at the province level in the context of the planned emissions reduction targets. We explore the possibility of the existence of a non-linear relationship between R&D expenditures and CO2 emissions with a non-parametric methodology, a fixed effect panel data quantile (FEQR) regression estimator applied to a panel of 30 provinces. We stratify the sample according to the …


Agricultural Groundcover Update December 2023, Justin Laycock Jan 2024

Agricultural Groundcover Update December 2023, Justin Laycock

Natural resources published reports

Summary

  • About 96% of the grainbelt had adequate vegetative groundcover (more than 50%) to prevent wind erosion in December 2023.
  • In the northern half of the grainbelt, a larger-than-average area has 51–60% groundcover, which is expected to decrease to below 50% over the summer.
  • Just under 4% of the grainbelt (553,000 ha) had less than 50% groundcover, which is inadequate to prevent wind erosion. West Midlands Ag Soil Zone had the highest risk of wind erosion and 11.4% of this farmland had inadequate groundcover.
  • Less than 0.5% of the grainbelt had a high to very high risk of wind erosion …


Life Cycle Assessment Of The Construction Process In A Mass Timber Structure, Mahboobeh Hemmati, Tahar Messadi, Hongmei Gu Jan 2024

Life Cycle Assessment Of The Construction Process In A Mass Timber Structure, Mahboobeh Hemmati, Tahar Messadi, Hongmei Gu

Architecture Faculty Publications and Presentations

Today, the application of green materials in the building industry is the norm rather than the exception and reflects an attempt to mitigate the sector’s environmental impacts. Mass timber is growing rapidly in the construction field because of its long span, speed of installation, lightness and toughness, carbon sequestration capabilities, renewability, fire rating, acoustic isolation, and thermal resistance. Mass timber is close to overtaking steel and concrete as the preferred material. The endeavor of this research is to quantitatively assess the ability of this green material to leverage the abatement of carbon emissions. Life cycle assessment (LCA) is a leading …


Reverse-Engineering Of Disinformation Campaigns During The War In Ukraine, Lora Pitman, Ava Baratz, Kelly Morgan, Marcy Alvarado Jan 2024

Reverse-Engineering Of Disinformation Campaigns During The War In Ukraine, Lora Pitman, Ava Baratz, Kelly Morgan, Marcy Alvarado

School of Cybersecurity Faculty Publications

Information operations have long been a part of warfare. Disinformation campaigns, in particular, are usually launched by states in order to mislead and confuse populations in adversarial countries, but also to obtain support for their actions from domestic audiences. These campaigns threaten human security, at the individual level, but also state- and even international security. The invasion of Ukraine by Russia came with a new wave of disinformation not only in Ukraine itself, but also in countries from various other continents. This paper studies the characteristics of the spread of disinformation from the first day of the war in February …


Optimal Network Analysis Through Vertex Order Coloring Of Intuitionistic Fuzzy Graph Operations, A. Meenakshi, S. Dhanushiya, Hong Qin, Maniyandy Elangovan Jan 2024

Optimal Network Analysis Through Vertex Order Coloring Of Intuitionistic Fuzzy Graph Operations, A. Meenakshi, S. Dhanushiya, Hong Qin, Maniyandy Elangovan

Data Science Faculty Publications

Intuitionistic fuzzy graphs IFGs are a powerful tool for modeling uncertainty and complex relationships. They offer versatile frameworks for addressing real-world challenges. In this research, we have introduced intuitionistic fuzzy vertex order coloring IFVOC and analyzed the alpha-strong (alpha str), beta-strong (beta str), and gamma-strong (gamma str) vertices through their degree. We explored important theorems based on the types of strong vertices, broadening the scope of our study. We analyzed multiple IFG products to determine the most optimal network based on some important metrics, including the weight and total number of alpha str vertices, the chromatic number, and the weight …


Large Offshore Wind Farms Have Minimal Direct Impacts On Air Quality, Maryam Golbazi, Cristina L. Archer Jan 2024

Large Offshore Wind Farms Have Minimal Direct Impacts On Air Quality, Maryam Golbazi, Cristina L. Archer

Data Science Faculty Publications

Wind power has rapidly grown over the past decade because it is clean, renewable, and abundant. However, wind farms can affect local weather and possibly alter the transport, diffusion, and concentration of air pollutants. Given the unprecedented expansion of offshore wind farms planned along the U.S. East Coast by the Bureau of Ocean Energy Management (BOEM), this study aims to investigate if and how those future offshore wind farms might directly affect air pollution along the densely populated East Coast, in particular, the concentrations of ozone (O3), fine particulate matter (PM2.5), sulfur dioxide (SO2), …


In Pursuit Of Consumption-Based Forecasting, Charles Chase, Kenneth B. Kahn Jan 2024

In Pursuit Of Consumption-Based Forecasting, Charles Chase, Kenneth B. Kahn

Marketing Faculty Publications

[Introduction] Today's most mature, most sophisticated, best-in-class forecasting is what we call consumption-based forecasting (CBF). In contrast, the least sophisticated companies typically do not forecast at all, but rather set financial targets based on management expectations. Companies beginning to use statistical forecasting techniques usually take a supply-centric orientation, relying on time series techniques applied to shipment and/or order history. The next stage of progression is to incorporate promotions data, economic data, and market data alongside supply-centric data so that regression and other advanced analytics can be used. Companies pursing CBF utilize even more advanced capabilities to capture, examine, and understand …


Nitrate Contamination In Two California Groundwater Basins: What Creates Disparities?, Catherine Protiva Jan 2024

Nitrate Contamination In Two California Groundwater Basins: What Creates Disparities?, Catherine Protiva

Scripps Senior Theses

Nitrate contamination is a major problem within California groundwater basins. A form of nitrogen, nitrates leach into groundwater aquifers from the surface where they remain for many decades. The most common source for the contaminant is agricultural sources like nitrogen fertilizer. Consequently, the problem is concentrated in regions of the state with a history of large-scale agricultural production. When water is pulled from contaminated basins and used as drinking water, the nitrates can cause serious negative health consequences, most commonly methemoglobinemia, also known as blue baby syndrome. In this thesis, I will examine what factors contribute to a region’s ability …


Bayesian Inference In Reinforcement Learning Neural Networks During A Markov Decision Processes?, Katherine Graham Jan 2024

Bayesian Inference In Reinforcement Learning Neural Networks During A Markov Decision Processes?, Katherine Graham

Scripps Senior Theses

The predictive mind theory proposes that brains work in a way that makes predictions about future stimuli to process information efficiently and accurately. Bayesian brain theory suggests that the brain utilizes Bayesian probability models to make predictions, while the free-energy minimization hypothesis proposes that these predictions are made to minimize energy or uncertainty, ensuring accurate perceptions. Vertechi et al. (2020) explored animal participants’ utilization of stimulus-bound strategy versus inference-based strategy to solve a Markov decision process with a 2-state environment, one of which is always active. These sites have a certain probability of switching to a different site and the …


A Generative Approach For Document Enhancement With Small Unpaired Data, Mohammad Shahab Uddin, Wael Khallouli, Andres Sousa-Poza, Samuel Kovacic, Jiang Li Jan 2024

A Generative Approach For Document Enhancement With Small Unpaired Data, Mohammad Shahab Uddin, Wael Khallouli, Andres Sousa-Poza, Samuel Kovacic, Jiang Li

Engineering Management & Systems Engineering Faculty Publications

Shipbuilding drawings, crafted manually before the digital era, are vital for historical reference and technical insight. However, their digital versions, stored as scanned PDFs, often contain significant noise, making them unsuitable for use in modern CAD software like AutoCAD. Traditional denoising techniques struggle with the diverse and intense noise found in these documents, which also does not adhere to standard noise models. In this paper, we propose an innovative generative approach tailored for document enhancement, particularly focusing on shipbuilding drawings. For a small, unpaired dataset of clean and noisy shipbuilding drawing documents, we first learn to generate the noise in …


Proof Of Principle For A Self-Governing Prediction And Forecasting Reward Algorithm, Jose Osvaldo Gonzalez-Hernandez, Jonathan Marino, Ted Rogers, Brandon Velasco Jan 2024

Proof Of Principle For A Self-Governing Prediction And Forecasting Reward Algorithm, Jose Osvaldo Gonzalez-Hernandez, Jonathan Marino, Ted Rogers, Brandon Velasco

Physics Faculty Publications

We use Monte Carlo techniques to simulate an organized prediction competition between a group of scientific experts acting under the influence of a "self-governing" prediction reward algorithm. Our aim is to illustrate the advantages of a specific type of reward distribution rule that is designed to address some of the limitations of traditional forecast scoring rules. The primary extension of this algorithm as compared with standard forecast scoring is that it incorporates measures of both group consensus and question relevance directly into the reward distribution algorithm. Our model of the prediction competition includes parameters that control both the level of …


Disentangling Accelerated Cognitive Decline From The Normal Aging Process And Unraveling Its Genetic Components: A Neuroimaging-Based Deep Learning Approach, Yulin Dai, Yu-Chun Hsu, Brisa S Fernandes, Kai Zhang, Xiaoyang Li, Nitesh Enduru, Andi Liu, Astrid M Manuel, Xiaoqian Jiang, Zhongming Zhao, Alzheimer’S Disease Neuroimaging Initiative Jan 2024

Disentangling Accelerated Cognitive Decline From The Normal Aging Process And Unraveling Its Genetic Components: A Neuroimaging-Based Deep Learning Approach, Yulin Dai, Yu-Chun Hsu, Brisa S Fernandes, Kai Zhang, Xiaoyang Li, Nitesh Enduru, Andi Liu, Astrid M Manuel, Xiaoqian Jiang, Zhongming Zhao, Alzheimer’S Disease Neuroimaging Initiative

Faculty, Staff and Student Publications

BACKGROUND: The progressive cognitive decline, an integral component of Alzheimer's disease (AD), unfolds in tandem with the natural aging process. Neuroimaging features have demonstrated the capacity to distinguish cognitive decline changes stemming from typical brain aging and AD between different chronological points.

OBJECTIVE: To disentangle the normal aging effect from the AD-related accelerated cognitive decline and unravel its genetic components using a neuroimaging-based deep learning approach.

METHODS: We developed a deep-learning framework based on a dual-loss Siamese ResNet network to extract fine-grained information from the longitudinal structural magnetic resonance imaging (MRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. …


Community Scientist Program Provides Bi-Directional Communication And Co-Learning Between Researchers And Community Members, Jessica Alvarado, Larkin L Strong, Birnur Buzcu-Guven, Leonetta B Thompson, Erica Cantu, Chelsea C Carrier, Chiamaka D Chukwu, Cassandra L Harris, Luz K Melendez, Crystal L Roberson, Angela M Ross, Sophia C Russell, Pablo Sanchez, Amirali Tahanan, Blair C Zdenek, Belinda M Reininger, Lorna H Mcneill Jan 2024

Community Scientist Program Provides Bi-Directional Communication And Co-Learning Between Researchers And Community Members, Jessica Alvarado, Larkin L Strong, Birnur Buzcu-Guven, Leonetta B Thompson, Erica Cantu, Chelsea C Carrier, Chiamaka D Chukwu, Cassandra L Harris, Luz K Melendez, Crystal L Roberson, Angela M Ross, Sophia C Russell, Pablo Sanchez, Amirali Tahanan, Blair C Zdenek, Belinda M Reininger, Lorna H Mcneill

Faculty, Staff and Student Publications

Community involvement in research is key to translating science into practice, and new approaches to engaging community members in research design and implementation are needed. The Community Scientist Program, established at the MD Anderson Cancer Center in Houston in 2018 and expanded to two other Texas institutions in 2021, provides researchers with rapid feedback from community members on study feasibility and design, cultural appropriateness, participant recruitment, and research implementation. This paper aims to describe the Community Scientist Program and assess Community Scientists' and researchers' satisfaction with the program. We present the analysis of the data collected from 116 Community Scientists …


Glacial Deposits, Vol. 48, 2024, Department Of Geography, Geology, And The Environment Jan 2024

Glacial Deposits, Vol. 48, 2024, Department Of Geography, Geology, And The Environment

Glacial Deposits

Newsletter of the Department of Geography, Geology, and the Environment


Recommendations To Internal Auditors Regarding The Auditing And Attestation Of Mathematical Programming Models, Jose Rincón, Greg Akai, Daryl Ono Jan 2024

Recommendations To Internal Auditors Regarding The Auditing And Attestation Of Mathematical Programming Models, Jose Rincón, Greg Akai, Daryl Ono

Librarian Publications & Presentations

Mathematical programming planning models increase operational efficiency and minimize operating costs, but the underlying mathematics generally is complex. Combinatorial optimization is technically sophisticated which requires a strong quantitative background to successfully implement. Most internal auditors will not have the technical training to critically assess the underlying mathematics of mathematical programming planning models, but the internal auditor can still provide insight and attestation which can increase the efficiency of mathematical programming planning models.


Classification Models Using Python In Industrial/Organizational Psychology, Beyza Ceylan Jan 2024

Classification Models Using Python In Industrial/Organizational Psychology, Beyza Ceylan

Williams Honors College, Honors Research Projects

Companies, industries, and places of business use artificial intelligence and statistics to predict the characteristics of their employees and staff. Data collected from these individuals is also used to make decisions about them regarding their work life, such as promotions, salaries, or within the hiring process. Two models that are commonly used throughout the field of psychology and specifically in industrial/organizational psychology are the linear regression and the logistic regression. Examining different classification models using Python shows the potential that there may be different models that are more accurate in their predictions of employee success, including a Random Forest model …


Crossing The “Valley Of Death”: How Climate Technology Entrepreneurs Navigate Relationships With Venture Capital Investors, Allison Lucas Jan 2024

Crossing The “Valley Of Death”: How Climate Technology Entrepreneurs Navigate Relationships With Venture Capital Investors, Allison Lucas

Wayne State University Dissertations

As the world faces the ongoing and intensifying impacts of climate change, a group of innovative changemakers known as climate tech entrepreneurs (CTEs) are working on climate adaptation, mitigation, and/or resilience efforts by brining innovative technologies to the global market (UNFCC, 2018; Endeavor 2022). To realize the full potential of these technologies—tools, techniques, specialized knowledge or skillsets—they must be developed, deployed, and implemented at scale (IPCC, 2000). To do this, CTEs require external funding support, especially during a crucial period of the start-up lifecycle known as the “valley of death”. In this period between development and commercialization, production costs and …


Virtual Reality & Pilot Training: Existing Technologies, Challenges & Opportunities, Tim Marron, Niall Dungan, Brian Mac Namee, Anna Donnla O'Hagan Jan 2024

Virtual Reality & Pilot Training: Existing Technologies, Challenges & Opportunities, Tim Marron, Niall Dungan, Brian Mac Namee, Anna Donnla O'Hagan

Journal of Aviation/Aerospace Education & Research

The introduction of virtual reality (VR) to flying training has recently gained much attention, with numerous VR companies, such as Loft Dynamics and VRpilot, looking to enhance the training process. Such a considerable change to how pilots are trained is a subject that warrants careful consideration. Examining the effect that VR has on learning in other areas gives us an idea of how VR can be suitably applied to flying training. Some of the benefits offered by VR include increased safety, decreased costs, and increased environmental sustainability. Nevertheless, some challenges ahead for developers to consider are negative transfer of learning, …


Medium Range Prediction Of U.S. Severe Convective Storms, Robert Fritzen Jan 2024

Medium Range Prediction Of U.S. Severe Convective Storms, Robert Fritzen

Graduate Research Theses & Dissertations

Severe convective storms (SCSs) are responsible for billions of dollars of losses in the United States each year through hazards such as large hail, damaging convective wind gusts, and tornadoes. While techniques for forecasting these SCSs have improved over the years, a majority of these improvements focus on short term forecasting and nowcasting techniques. Little work has been done to analyze the recent advances in numerical weather prediction techniques, and to leverage these advances to the prediction of SCSs at the medium range (defined herein as lead-day 4--8). The primary objectives of this dissertation research are to: 1) explore the …


Towards A More Engaged Democracy: Using Statistical Methods To Detect Election Fraud In The 2022 Philippine National Elections, Juan Miguel Cardaño, Bryan Patrick Mande, Seth William Tionko, Aldrich Ellis C. Asuncion, Jeric C. Briones Jan 2024

Towards A More Engaged Democracy: Using Statistical Methods To Detect Election Fraud In The 2022 Philippine National Elections, Juan Miguel Cardaño, Bryan Patrick Mande, Seth William Tionko, Aldrich Ellis C. Asuncion, Jeric C. Briones

Mathematics Faculty Publications

This paper aims to show how citizens can further participate in the elections, aside from just voting. Given the accusations of fraud, this study demonstrates how existing election fraud detection methods can be used in the 2022 Philippine National Elections (PNE) context. Specifically, histograms known as 2D vote turnout distributions were first utilized to model the frequency of the winner's percentage of votes based on the voter turnout in each electoral unit, with key parameters introduced to detect fraud. Vote turnout distributions were then simulated using parametric models involving the aforementioned fraud parameters, with the goal of replicating the actual …


Optimizing Php Api Calls With Pagination And Caching, Parsharam Reddy Sudda Jan 2024

Optimizing Php Api Calls With Pagination And Caching, Parsharam Reddy Sudda

Dissertations, Master's Theses and Master's Reports

The Keweenaw Time Traveler (KeTT) project is devoted to mapping the historical and social landscapes of the Keweenaw Peninsula. During the project, it was discovered that the server-side performance needed improvement. To address this issue, the "Optimizing PHP API Calls with Pagination and Caching" initiative was launched. This initiative focused on refining API calls, implementing server caching and pagination, and fortifying security against common vulnerabilities. The project successfully mitigated risks associated with SQL Injection and XSS through meticulous code enhancements while improving error handling. Additionally, the introduction of Scroll-Induced Pagination optimized data delivery, significantly reducing response times, and elevating the …


Life Cycle Greenhouse Gas Emissions In Maize No-Till Agroecosystems In Southern Brazil Based On A Long-Term Experiment, Guilherme Rosa Da Silva, Adam J. Liska, Cimelio Bayer Jan 2024

Life Cycle Greenhouse Gas Emissions In Maize No-Till Agroecosystems In Southern Brazil Based On A Long-Term Experiment, Guilherme Rosa Da Silva, Adam J. Liska, Cimelio Bayer

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Brazilian agriculture is constantly questioned concerning its environmental impacts, particularly greenhouse gas (GHG) emissions. This research study used data from a 34-year field experiment to estimate the life cycle GHG emissions intensity of maize production for grain in farming systems under no-tillage (NT) and conventional tillage (CT) combined with Gramineae (oat) and legume (vetch) cover crops in southern Brazil. We applied the Feedstock Carbon Intensity Calculator for modeling the “field-to-farm gate” emissions with measured annual soil N2O and CH4 emissions data. For net CO2 emissions, increases in soil organic C (SOC) were applied as a proxy, …


Listening To The Voices Of America, Kathryn J. Edin, Corey D. Fields, David B. Grusky, Jure Leskovec, Marybeth J. Mattingly, Kristen M. Olson, Charles Varner Jan 2024

Listening To The Voices Of America, Kathryn J. Edin, Corey D. Fields, David B. Grusky, Jure Leskovec, Marybeth J. Mattingly, Kristen M. Olson, Charles Varner

Department of Sociology: Faculty Publications

We make the case for building a permanent public-use platform for conducting and analyzing immersive interviews on the everyday lives of Americans. The American Voices Project (AVP)—a widely watched experiment with this new platform—provides important early evidence on its promise. The articles in this issue reveal that, although public-use interview datasets obviously cannot meet all research needs, they do provide new opportunities to study small or hidden populations, new or emerging social problems, reactions to ongoing social crises, submerged values and attitudes, and many other aspects of American life. We conclude that a permanent AVP platform would help build an …


Measuring Changes In Pork Demand, Welfare Effects, And The Role Of Information Sources In The Event Of An African Swine Fever Outbreak In The United States, Pratyoosh Kashyap, Jordan F. Suter, Sophie C. Mckee Jan 2024

Measuring Changes In Pork Demand, Welfare Effects, And The Role Of Information Sources In The Event Of An African Swine Fever Outbreak In The United States, Pratyoosh Kashyap, Jordan F. Suter, Sophie C. Mckee

United States Department of Agriculture Wildlife Services: Staff Publications

African swine fever (ASF) has never been detected in the United States, but the current global outbreak threatens to change that. Although ASF poses no known risk to human health and is not a food safety concern, little is known about the response in U.S. consumer demand in case of an outbreak. We use an online survey experiment, following the one-and-one-half-bound dichotomous choice contingent valuation approach to estimate changes in consumers’ willingness to pay for pork in case of an ASF outbreak. Using these estimates, we find that demand for unprocessed pork (processed pork) products in the U.S. is predicted …


Growing Up Sustainable? Politics Of Race And Youth In Urbanplan, Copenhagen, Max Ritts, Rebecca Rutt Jan 2024

Growing Up Sustainable? Politics Of Race And Youth In Urbanplan, Copenhagen, Max Ritts, Rebecca Rutt

Geography

This paper considers how racialized youth in Denmark negotiate sustainability amid contexts marked by intersecting forms of economic restructuring, progressive neoliberalism, white ethno-nationalism, and green urban planning. Urbanplan is a low-income, notoriously “troubled” Copenhagen neighborhood where we conducted fieldwork for 7 months (2019-2020) with fifteen male youth, aged 17-21. Using ethnography, policy reviews, and interviews with city social workers, we explore how intimate experiences of nature, group-identity, and place attachment here relate to and depart from the structural forces actively reshaping the neighborhood. Our analysis combines Cindi Katz's intersectional political economy approach with recent work on green gentrification, Critical Utopian …