Federal charges filed against operators of Houston stash house

Five individuals in the United States illegally have been taken into custody following the discovery of nearly 100 undocumented aliens in a suburban Houston res

Read full article at: https://www.justice.gov May 3, 2021

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    What GAO Found The Social Security Administration's (SSA) administrative law judges review, process, and adjudicate requests for hearings on disability benefits. In 2007, the agency set an expectation—which SSA reported was based on trend data and some regional managers' input—for judges to issue 500-700 dispositions (decisions and dismissals) each year, and the extent to which they have met this expectation has varied over time. SSA did not document the expectation-setting process in 2007, nor has it formally reviewed the expectation since. Judges in discussion groups held by GAO questioned the basis of the expectation and 87 percent of judges GAO surveyed (47 of 54) said the expectation was too high. The extent to which judges met the annual and related expectations has fluctuated over the years (see figure). Without periodic reviews, SSA cannot be assured that its expectations appropriately allow judges to balance productivity with other expectations, such as quality, given changing conditions over time. Administrative Law Judges Who Met or Exceeded SSA's Annual Productivity Expectation, Fiscal Years 2014-2020 Judges in selected hearing offices cited a variety of factors affecting their ability to meet the annual expectation. The top factor cited by judges GAO surveyed was the size of case files, which have increased five-fold on average since the expectation was established, according to SSA data. The COVID-19 pandemic introduced other factors in 2020, resulting in fewer hearings being conducted. SSA monitors judges' productivity and takes various actions when expectations are not met, ranging from informal conversations to formal discipline. In addition, judges in 11 of 13 discussion groups viewed telework restrictions as a consequence for not meeting expectations. Additionally, judges GAO surveyed reported feeling pressured to meet the expectations. For instance, 87 percent of judges surveyed (47 of 54) said that SSA placed too much emphasis on productivity, and some expressed concerns about their work quality and work-life balance. SSA officials said they do not formally seek feedback from judges on the expectations. However, without feedback or other gauges of pressure, SSA lacks information that could help it appropriately balance timely case processing while maintaining high-quality work and employee morale. Why GAO Did This Study SSA's approximately 1,350 judges play a major role in processing and adjudicating requests for hearings to help ensure individuals who do not agree with the determination on their claim for Social Security disability benefits receive due process. SSA receives hundreds of thousands of hearing requests each year and has historically had a large backlog. GAO was asked to review SSA's productivity expectations for its judges. This report examines (1) how SSA set productivity expectations for judges and the extent to which judges have met them over time, (2) reported factors affecting the ability of judges in selected offices to meet the annual productivity expectation, and (3) SSA's management of judges' productivity. GAO obtained and analyzed SSA data on judges' productivity from fiscal years 2005-2020; surveyed and held 13 virtual discussion groups with judges in six hearing offices selected for geographic location, average productivity, and average case size; reviewed relevant federal laws and agency policies and documents; and interviewed officials from SSA and the association representing judges.
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Forbearance was also more common among borrowers at a greater risk of mortgage default—specifically, first-time, minority, and low- and moderate-income homebuyers with mortgages insured by the Federal Housing Administration and rural homebuyers with loans guaranteed by the Rural Housing Service (see fig. 1). Figure 1: Estimated Percentage of Single-Family Mortgage Loans in Forbearance, by Loan Type (January 2020–February 2021) A small percentage of borrowers who missed payments during the pandemic have not used forbearance—less than 1 percent of those covered by the CARES Act. Yet, borrowers who have not used forbearance may be at a greater risk of default and foreclosure, according to GAO's analysis of the National Mortgage Database. For example, these borrowers tended to have lower subprime credit scores, indicating an elevated risk of default, compared to borrowers who were current or in forbearance, who tended to have higher prime or near prime credit scores. Federal agencies and the government-sponsored enterprises Fannie Mae and Freddie Mac (the enterprises) have taken steps to make these borrowers aware of forbearance options, such as through direct phone calls and letters. In addition, the Consumer Financial Protection Bureau (CFPB) amended mortgage servicing rules in June 2021 to require servicers to discuss forbearance options with borrowers shortly after any delinquency. Foreclosures declined significantly during the pandemic because of federal moratoriums that prohibited foreclosures. The number of mortgages entering foreclosure decreased by about 85 percent on a year-over-year basis from June 2019 to June 2020 and remained as low through February 2021, according to mortgage data provider Black Knight (see fig. 2). Figure 2: Number of Single-Family Mortgage Loans Entering Foreclosure, by Month (June 2019–February 2021) Note: Foreclosure data were only available through February 2021 at the time of our review. The number of new foreclosures includes vacant and abandoned properties and non-federally backed loans, which the CARES Act did not cover. Federal entities have taken additional steps to limit pandemic-related mortgage defaults and foreclosures. Federal housing agencies and the enterprises have expanded forbearance options to provide borrowers with additional time to enter and remain in forbearance. In addition, they streamlined and introduced new loss mitigation options to help borrowers reinstate their loans after forbearance, including options to defer missed payments until the end of a mortgage. Borrowers in extended forbearances generally have large expected repayments—an average of $8,300 as of February 2021, according to the National Mortgage Database. As a result, delinquent borrowers exiting forbearance have most commonly deferred repayment, according to the Mortgage Bankers Association. Further, CFPB's amended mortgage servicing rules allow servicers to streamline processing of loss mitigation actions and establish procedural safeguards to help limit avoidable foreclosures until January 1, 2022. The risk of a spike in defaults and foreclosures is further mitigated by the relatively strong equity position of borrowers due to rapid home price appreciation. Home equity—or the difference between a home's current value and any outstanding loan balances—can help borrowers with ongoing hardships avoid foreclosure by allowing them to refinance their mortgage or sell their home to pay off the remaining balance. According to GAO's analysis of the National Mortgage Database, few borrowers (about 2 percent) who were in forbearance or delinquent in February 2021 did not have home equity after accounting for home price appreciation. By comparison, during the peak of foreclosures in 2011 after the 2007–2009 financial crisis, about 17 percent of all borrowers and 44 percent of delinquent borrowers had no home equity (see fig. 3). Figure 3: Estimated Percentage of Single-Family Mortgage Borrowers without Home Equity as of 2020 and 2011, by Loan Type and Status Why GAO Did This Study Millions of mortgage borrowers continue to experience financial challenges and potential housing instability during the COVID-19 pandemic. To address these concerns, Congress, federal agencies, and the enterprises provided borrowers with options to temporarily suspend their mortgage payments and placed a moratorium on foreclosures. Both provisions begin to expire in the coming months. The CARES Act includes a provision for GAO to monitor federal efforts related to COVID-19. This report examines (1) the extent to which mortgage forbearance may have contributed to housing stability during the pandemic, (2) federal efforts to promote awareness of forbearance among delinquent borrowers, and (3) federal efforts to limit mortgage default and foreclosure risks after federal mortgage forbearance and foreclosure protections expire. GAO analyzed data on mortgage performance and the characteristics of borrowers who used forbearance from January 2020 to February 2021 using the National Mortgage Database (a federally managed, generalizable sample of single-family mortgages). GAO also reviewed data from Black Knight and the Mortgage Bankers Association on foreclosures and forbearance repayment. In addition, GAO interviewed representatives of federal entities about efforts to communicate with borrowers and limit default and foreclosure risks. To highlight potential risks, GAO also analyzed current trends in home equity among delinquent borrowers relative to the 2007–2009 financial crisis. For more information, contact John Pendleton at (202) 512-8678 or PendletonJ@gao.gov.
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    Why This Matters Air quality sensors are essential to measuring and studying pollutants that can harm public health and the environment. Technological improvements have led to smaller, more affordable sensors as well as satellite-based sensors with new capabilities. However, ensuring the quality and appropriate interpretation of sensor data can be challenging. The Technology What is it? Air quality sensors monitor gases, such as ozone, and particulate matter, which can harm human health and the environment. Federal, state, and local agencies jointly manage networks of stationary air quality monitors that make use of sensors. These monitors are expensive and require supporting infrastructure. Officials use the resulting data to decide how to address pollution or for air quality alerts, including alerts during wildfires or on days with unhealthy ozone levels. However, these networks can miss pollution at smaller scales and in rural areas. They generally do not measure air toxics—more localized pollutants that may cause cancer and chronic health effects—such as ethylene oxide and toxic metals. Two advances in sensor technologies may help close these gaps. First, newer low-cost sensors can now be deployed virtually anywhere, including on fences, cars, drones, and clothing (see fig. 1). Researchers, individuals, community groups, and private companies have started to deploy these more affordable sensors to improve their understanding of a variety of environmental and public health concerns. Second, federal agencies have for decades operated satellites with sensors that monitor air quality to understand weather patterns and inform research. Recent satellite launches deployed sensors with enhanced air monitoring capabilities, which researchers have begun to use in studies of pollution over large areas. Figure 1. There are many types of air quality sensors, including government-operated ground-level and satellite-based sensors, as well as low-cost commercially available sensors that can now be used on a variety of platforms, such as bicycles, cars, trucks, and drones. How does it work? Low-cost sensors use a variety of methods to measure air quality, including lasers to estimate the number and size of particles passing through a chamber and meters to estimate the amount of a gas passing through the sensor. The sensors generally use algorithms to convert raw data into useful measurements (see fig. 2). The algorithms may also adjust for temperature, humidity and other conditions that affect sensor measurements. Higher-quality devices can have other features that improve results, such as controlling the temperature of the air in the sensors to ensure measurements are consistent over time. Sensors can measure different aspects of air quality depending on how they are deployed. For example, stationary sensors measure pollution in one location, while mobile sensors, such as wearable sensors carried by an individual, reflect exposure at multiple locations. Satellite-based sensors generally measure energy reflected or emitted from the earth and the atmosphere to identify pollutants between the satellite and the ground. Some sensors observe one location continuously, while others observe different parts of the earth over time. Multiple sensors can be deployed in a network to track the formation, movement, and variability of pollutants and to improve the reliability of measurements. Combining data from multiple sensors can increase their usefulness, but it also increases the expertise needed to interpret the measurements, especially if data come from different types of sensors. Figure 2. A low-cost sensor pulls air in to measure pollutants and stores information for further study. How mature is it? Sensors originally developed for specific applications, such as monitoring air inside a building, are now smaller and more affordable. As a result, they can now be used in many ways to close gaps in monitoring and research. For example, local governments can use them to monitor multiple sources of air pollution affecting a community, and scientists can use wearable sensors to study the exposure of research volunteers. However, low-cost sensors have limitations. They operate with fewer quality assurance measures than government-operated sensors and vary in the quality of data they produce. It is not yet clear how newer sensors should be deployed to provide the most benefit or how the data should be interpreted. Some low-cost sensors carry out calculations using artificial intelligence algorithms that the designers cannot always explain, making it difficult to interpret varying sensor performance. Further, they typically measure common pollutants, such as ozone and particulate matter. There are hundreds of air toxics for which additional monitoring using sensors could be beneficial. However, there may be technical or other challenges that make it impractical to do so. Older satellite-based sensors typically provided infrequent and less detailed data. But newer sensors offer better data for monitoring air quality, which could help with monitoring rural areas and pollution transport, among other benefits. However, satellite-based sensor data can be difficult to interpret, especially for pollution at ground level. In addition, deployed satellite-based sensor technologies currently only measure a few pollutants, including particulate matter, ozone, sulfur dioxide, nitrogen dioxide, formaldehyde, and carbon monoxide. Opportunities Improved research on health effects. The ability to track personal exposure and highly localized pollution could improve assessments of public health risks. Expanded monitoring. More dense and widespread monitoring could help identify pollution sources and hot spots, in both urban and rural areas. Enhanced air quality management. Combined measurements from stationary, mobile, and satellite-based sensors can help officials understand and mitigate major pollution issues, such as ground-level ozone and wildfire smoke. Community engagement. Lower cost sensors open up new possibilities for community engagement and citizen science, which is when the public conducts or participates in the scientific process, such as by making observations, collecting and sharing data, and conducting experiments. Challenges Performance. Low-cost sensors have highly variable performance that is not well understood, and their algorithms may not be transparent. Low-cost sensors operated by different users or across different locations may have inconsistent measurements. Interpretation. Expertise may be needed to interpret sensor data. For example, sensors produce data in real time that may be difficult to interpret without health standards for short-term exposures. Data management. Expanded monitoring will create large amounts of data with inconsistent formatting, which will have to be stored and managed. Alignment with needs. Few of the current low-cost and satellite-based sensors measure air toxics. In addition, low-income communities, which studies show are disproportionally harmed by air pollution, may still face challenges deploying low-cost sensors. Policy Context and Questions How can policymakers leverage new opportunities for widespread monitoring, such as citizen science, while also promoting appropriate use and interpretation of data? How can data from a variety of sensors be integrated to better understand air quality issues, such as environmental justice concerns, wildfires, and persistent ozone problems? How can research and development efforts be aligned to produce sensors to monitor key pollutants that are not widely monitored, such as certain air toxics? For more information, contact Karen Howard at (202) 512-6888 or HowardK@gao.gov.
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