skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: A Framework to Develop Interventions to Address Labor Exploitation and Trafficking: Integration of Behavioral and Decision Science within a Case Study of Day Laborers
This paper describes a process that integrates behavioral and decision science methods to design and evaluate interventions to disrupt illicit behaviors. We developed this process by extending a framework used to study systems with uncertain outcomes, where only partial information is observable, and wherein there are multiple participating parties with competing goals. The extended framework that we propose builds from artefactual data collection, thematic analysis, and descriptive analysis, toward predictive modeling and agent-based modeling. We use agent-based modeling to characterize and predict interactions between system participants for the purpose of improving our understanding of interventional targets in a virtual environment before piloting them in the field. We apply our extended framework to an exploratory case study that examines the potential of worker centers as a venue for deploying interventions to address labor exploitation and human trafficking. This case study focuses on reducing wage theft, the most prevalent form of exploitation experienced by day laborers and applies the first three steps of the extended framework. Specifically, the case study makes a preliminary assessment of two types of social interventions designed to disrupt exploitative processes and improve the experiences of day laborers, namely: (1) advocates training day laborers about their workers’ rights and options that they have for addressing wage theft and (2) media campaigns designed to disseminate similar educational messages about workers’ rights and options to address wage theft through broadcast channels. Applying the extended framework to this case study of day laborers at a worker center demonstrates how digital technology could be used to monitor, evaluate, and support collaborations between worker center staff and day laborers. Ideally, these collaborations could be improved to mitigate the risks and costs of wage theft, build trust between worker center stakeholders, and address communication challenges between day laborers and employers, in the context of temporary work. Based on the application of the extended framework to this case study of worker center day laborers, we discuss how next steps in the research framework should prioritize understanding how and why employers make decisions to participate in wage theft and the potential for restorative justice and equity matching as a relationship model for employers and laborers in a well-being economy.  more » « less
Award ID(s):
2039983
PAR ID:
10463281
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
Societies
Volume:
13
Issue:
4
ISSN:
2075-4698
Page Range / eLocation ID:
96
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract Immigrant day laborers routinely experience exploitative behaviors as part of their employment. These day laborers perceive the exploitation they experience in the context of their immigration histories and in the context of their long-term goals for better working and living conditions. Using mixed methods, over three data collection periods in 2016, 2019 and 2020, we analyze the work experiences of immigrant day laborers in Houston and Austin, Texas. We report how workers evaluate precarious jobs and respond to labor exploitation in an informal labor market. We also discuss data from a worker rights training intervention conducted through a city-sponsored worker center. We discuss the potential for worker centers to be a convening and remediation space for workers and employers. Worker centers offer a potential space for informal intervention into wage theft and work safety violations by regulating the hiring context where day laborers meet employers. 
    more » « less
  2. Home care workers (HCWs) are professionals who provide care to older adults and people with disabilities at home. However, HCWs are vulnerable and especially susceptible to wage theft, or not being paid their legally-entitled wages in full by their employers. Prior work has examined other low-wage work settings to show how technology is designed and deployed has the potential to both cause and address wage theft. We extend this work by examining the relationship between technology and wage theft in the home care context. We collaborated closely with a local grassroots organization to conduct interviews with workers and labor, legal, and payroll experts. We uncovered how the complex, volatile, and diverse nature of home care complicates the errors in time-tracking systems. Through design provocations and focus groups with workers and experts, we also investigated the potential of technology as a part of broader efforts to curb wage theft through educating and empowering isolated HCWs. While we found that approachable design could reduce errors in existing systems, make employer processes more transparent, and help workers exchange knowledge to build collective power, we also discuss concerns around burden, privacy, and accountability when designing technologies for HCWs and other low-wage workers. 
    more » « less
  3. null (Ed.)
    Social media has become an effective recruitment tool for higher-waged and white-collar professionals. Yet, past studies have questioned its effectiveness for the recruitment of lower-waged workers. It is also unclear whether or how employers leverage social media in their recruitment of low-wage job seekers, and how social media could better support the needs of both stakeholders. Therefore, we conducted 15 semi-structured interviews with employers of low-wage workers in the U.S. We found that employers: use social media, primarily Facebook, to access large pools of active low-wage job seekers; and recognize indirect signals about low-wage job seekers’ commitment and job readiness. Our work suggests that there remains a visible, yet unaddressed power imbalance between low-wage workers and employers in the use of social media, which risks further destabilizing the precarious labor market. 
    more » « less
  4. The food and agriculture industries are critical to the U.S. economy, ensuring the daily food supply while facing significant challenges. These issues include ethical concerns related to labor exploitation and the need to improve resilience against disruptions. Addressing these issues offers an opportunity to create supply chains that are both more ethical and more resilient. This dissertation focuses on two interconnected aspects of agricultural supply chains. The first examines strategies for disrupting exploitative labor practices and ensuring better protection for farm workers. The second explores methods to enhance the resilience of ethical supply chains against various disruptions, including natural disasters and labor shortages. Together, these aspects aim to contribute to the development of agricultural supply chains that are both ethically sound and resilient to disruptions. Although farm workers play an essential role in the success of these industries, they are vulnerable to labor exploitation and trafficking. Labor violations affecting these workers often go undetected due to limited government resources for inspection. Furthermore, many farm workers face barriers to disclosing their poor working conditions due to their immigration status and mistrust of law enforcement, making them even more susceptible to exploitation. To address this issue, we conducted research to provide strategies for government agencies involved in the H-2A visa program and the screening of H-2A employers to prioritize workplaces for inspection. In the first study, we employed multilevel zero-inflated negative binomial regression analysis to extract patterns and identify factors correlated with detecting H-2A labor violations. We provide suggestions for improving inspection strategies based on our research results. This involved identifying high-risk locations and labor-intensive worksites with a greater likelihood of labor violations and emphasizing the importance of allocating sufficient task force funding and resources to prioritize inspections in these areas. Labor trafficking networks in U.S. agricultural supply chains exploit vulnerable workers, including migrants and unauthorized laborers, while evading detection through complex structures, making them difficult to disrupt. In the second study, we developed a comprehensive labor trafficking network model that maps the intricate connections and operations of these networks. Using a bi-level integer programming approach, we optimized intervention strategies to disrupt trafficking operations, balancing resource constraints with the need for maximum impact. By employing K-means clustering, we classified interventions based on their effectiveness, providing clear, data-driven guidance for anti-trafficking agencies to prioritize efforts and allocate resources efficiently. This approach offers a powerful tool for enhancing detection and improving the overall effectiveness of anti-trafficking initiatives in limited resource environments. The importance of food and agricultural supply chains in our daily lives cannot be emphasized enough. While the prior two studies sought to disrupt exploitative work conditions in agricultural supply chains, this dissertation also seeks to help supply chains that are operating ethically do so in an effective manner. Any disruption in these chains can lead to severe consequences, from food shortages to economic instability. Therefore, it is critical to develop effective strategies to mitigate the impact of disruptions in these non-exploitative supply chains. In the third study, we developed a scenario-based two-stage stochastic model to mitigate the impact of multiple disruptions in agricultural supply chains. This approach enables a detailed evaluation of strategies such as multi-sourcing and the use of backup facilities to reduce disruption impacts. The model incorporates flexibility to handle both partial and full facility disruptions, while accounting for disruptions affecting both primary and backup facilities to provide a comprehensive analysis of supply chain vulnerability and recovery. By employing a multi-period time horizon, the model evaluates supply chain performance over time, considering random disruption start times and the possibility of simultaneous disruptions across multiple echelons with varying severity. The analysis highlights the challenges posed by multiple sources of uncertainty in supply chain decision-making and emphasizes the need for further research to develop actionable strategies for improving resilience in agricultural supply chains. 
    more » « less
  5. Why do social computing projects aimed at alleviating social inequality fail? This paper investigates this question through a qualitative interview study with 25 individuals working to address the problem of wage theft in the United States (US) context. Our analyses uncover failures at three levels or scales of interaction: one, failures at the individual level of technology adoption; two, relational failures (i.e., the anti-labor worker/employer dynamic in the US); and three, institutional or macro-level failures. Taken together, these various failings point to larger, structural forces that negatively fate pro-labor projects’ trajectories – i.e., capitalism. Capitalism's incarnations in the US play a significant and at times harsh grip in steering the path of social computing design projects. In this paper, we untangle the relationship between capitalism and social computing, providing an analytic framework to tease apart this complex relationship, the lessons learned from our empirical data, as well as ways forward for future, pro-labor, social computing projects. 
    more » « less