{"componentChunkName":"component---node-modules-narative-gatsby-theme-novela-src-templates-article-template-tsx","path":"/introducing-the-cddl-blog!","result":{"data":{"allSite":{"edges":[{"node":{"siteMetadata":{"name":"MIT Civic Data Design Lab"}}}]}},"pageContext":{"article":{"id":"b913ccf7-d482-50f8-8d7d-67ed0f6019b5","slug":"/introducing-the-cddl-blog!","secret":false,"title":"Introducing the CDDL Blog! ","author":"Tess McCann","date":"May 15th, 2020","dateForSEO":"2020-05-15T00:00:00.000Z","timeToRead":1,"excerpt":"Since March, we at the Civic Data Design Lab (CDDL) have been collecting and analyzing data surrounding the COVID-19 pandemic. Our work has…","canonical_url":null,"subscription":true,"body":"function _extends() { _extends = Object.assign || function (target) { for (var i = 1; i < arguments.length; i++) { var source = arguments[i]; for (var key in source) { if (Object.prototype.hasOwnProperty.call(source, key)) { target[key] = source[key]; } } } return target; }; return _extends.apply(this, arguments); }\n\nfunction _objectWithoutProperties(source, excluded) { if (source == null) return {}; var target = _objectWithoutPropertiesLoose(source, excluded); var key, i; if (Object.getOwnPropertySymbols) { var sourceSymbolKeys = Object.getOwnPropertySymbols(source); for (i = 0; i < sourceSymbolKeys.length; i++) { key = sourceSymbolKeys[i]; if (excluded.indexOf(key) >= 0) continue; if (!Object.prototype.propertyIsEnumerable.call(source, key)) continue; target[key] = source[key]; } } return target; }\n\nfunction _objectWithoutPropertiesLoose(source, excluded) { if (source == null) return {}; var target = {}; var sourceKeys = Object.keys(source); var key, i; for (i = 0; i < sourceKeys.length; i++) { key = sourceKeys[i]; if (excluded.indexOf(key) >= 0) continue; target[key] = source[key]; } return target; }\n\n/* @jsx mdx */\nvar _frontmatter = {\n  \"title\": \"Introducing the CDDL Blog! \",\n  \"author\": \"Tess McCann\",\n  \"date\": \"2020-05-15T00:00:00.000Z\",\n  \"tags\": [\"General\"],\n  \"hero\": \"images/screen-shot-2020-05-15-at-3.21.28-am.png\"\n};\n\nvar makeShortcode = function makeShortcode(name) {\n  return function MDXDefaultShortcode(props) {\n    console.warn(\"Component \" + name + \" was not imported, exported, or provided by MDXProvider as global scope\");\n    return mdx(\"div\", props);\n  };\n};\n\nvar layoutProps = {\n  _frontmatter: _frontmatter\n};\nvar MDXLayout = \"wrapper\";\nreturn function MDXContent(_ref) {\n  var components = _ref.components,\n      props = _objectWithoutProperties(_ref, [\"components\"]);\n\n  return mdx(MDXLayout, _extends({}, layoutProps, props, {\n    components: components,\n    mdxType: \"MDXLayout\"\n  }), mdx(\"p\", null, \"Since March, we at the Civic Data Design Lab (CDDL) have been collecting and analyzing data surrounding the COVID-19 pandemic. Our work has always been about understanding data and using it to call attention to the needs and interests of citizens on the margins of policy development. The global pandemic, and its quantitative nature, has made this mission all the more crucial. COVID-19 is exposing existing inequalities in our country and across the globe. We urgently must document these disparities as they emerge to have a chance of addressing them.\"), mdx(\"p\", null, \"We are starting this blog in order to share the work we\\u2019re doing with a larger audience. We join a large community of scientists, designers, and urbanists around the world who are already engaged in open conversations about COVID-19 through the lens of its data\\u2014its nuances, its stories, and its calls to action. As in our other projects, we\\u2019re experimenting with collection tools and visualization strategies that allow us to highlight phenomena that might otherwise be overlooked.\"), mdx(\"p\", null, \"Our first post highlights how tricky it is to draw informed conclusions from COVID-19 data. Upcoming posts will delve into the inequalities of the outbreak, particularly how testing opportunities relate to income levels across the country.\"), mdx(\"p\", null, \"As the situation with COVID-19 evolves, so will this blog. We hope to use this space to start conversations toward change and we look forward to the dialogues that come from it.\"));\n}\n;\nMDXContent.isMDXComponent = 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At MIT, she is researching the use of history and historic buildings in large-scale urban developments and hopes to write her thesis on the topic. She enjoys reading critical cartographic and psychogeographic theory, and in her spare time makes maps in this tradition.  Before MIT, Tess worked at Pentagram Design as a project manager and strategist. She had the pleasure of working with the Brearley Communications, Admissions, and Development Departments on the new admissions and capital campaign materials in 2016 and 2017. In addition to working with Brearley, she oversaw the development of logos and other design assets for Yale University (her other alma mater), Mastercard, the American Museum of Natural History, the Poetry Foundation, the Broad Institute of MIT and Harvard, and Central Park Conservancy.  Tess graduated with honors from Yale, where she holds a bachelor’s degree in history, with a specific focus on 19th Century German militarism. Her thesis was a historiographical biography of the German general Helmuth von Moltke, and included original translations of official German records that are held in the Yale libraries. In 2014, she won the Acheson Prize, Yale’s top award for written academic work for her essay, 'The Historiography of Postwar and Contemporary Histories of the Outbreak of World War I'. She continues to practice her German, though admittedly it’s a bit eingerostet.","id":"05252285-5608-5772-b27d-9a2379f47492","name":"Tess 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","canonicalUrl":null,"mailchimp":"","next":[{"id":"a6247539-4599-5fb1-b7da-0252c41ae787","slug":"/who-cares-about-covid-19","secret":false,"title":"WHO CARES about COVID-19?","author":"Brian Williams","date":"August 30th, 2020","dateForSEO":"2020-08-30T00:00:00.000Z","timeToRead":3,"excerpt":"Is Section 18115 really doing anything? On June 4th, the U.S. Department of Health and Human Services (HHS) released new guidance requiring…","canonical_url":null,"subscription":true,"body":"function _extends() { _extends = Object.assign || function (target) { for (var i = 1; i < arguments.length; i++) { var source = arguments[i]; for (var key in source) { if (Object.prototype.hasOwnProperty.call(source, key)) { target[key] = source[key]; } } } return target; }; return _extends.apply(this, arguments); }\n\nfunction _objectWithoutProperties(source, excluded) { if (source == null) return {}; var target = _objectWithoutPropertiesLoose(source, excluded); var key, i; if (Object.getOwnPropertySymbols) { var sourceSymbolKeys = Object.getOwnPropertySymbols(source); for (i = 0; i < sourceSymbolKeys.length; i++) { key = sourceSymbolKeys[i]; if (excluded.indexOf(key) >= 0) continue; if (!Object.prototype.propertyIsEnumerable.call(source, key)) continue; target[key] = source[key]; } } return target; }\n\nfunction _objectWithoutPropertiesLoose(source, excluded) { if (source == null) return {}; var target = {}; var sourceKeys = Object.keys(source); var key, i; for (i = 0; i < sourceKeys.length; i++) { key = sourceKeys[i]; if (excluded.indexOf(key) >= 0) continue; target[key] = source[key]; } return target; }\n\n/* @jsx mdx */\nvar _frontmatter = {\n  \"title\": \"WHO CARES about COVID-19?\",\n  \"author\": \"Brian Williams\",\n  \"date\": \"2020-08-30T00:00:00.000Z\",\n  \"tags\": [\"Covid\", \"Data\", \"Health\", \"Race\", \"Visualization\"],\n  \"hero\": \"images/pic-for-2nd-article-cares.png\"\n};\n\nvar makeShortcode = function makeShortcode(name) {\n  return function MDXDefaultShortcode(props) {\n    console.warn(\"Component \" + name + \" was not imported, exported, or provided by MDXProvider as global scope\");\n    return mdx(\"div\", props);\n  };\n};\n\nvar layoutProps = {\n  _frontmatter: _frontmatter\n};\nvar MDXLayout = \"wrapper\";\nreturn function MDXContent(_ref) {\n  var components = _ref.components,\n      props = _objectWithoutProperties(_ref, [\"components\"]);\n\n  return mdx(MDXLayout, _extends({}, layoutProps, props, {\n    components: components,\n    mdxType: \"MDXLayout\"\n  }), mdx(\"p\", null, mdx(\"strong\", {\n    parentName: \"p\"\n  }, \"Is Section 18115 really doing anything?\")), mdx(\"p\", null, \"On June 4th, the U.S. Department of Health and Human Services (HHS) released new guidance requiring laboratories to include relevant demographic data, such as age and race, on every COVID-19 test. As specified in the Coronavirus Aid, Relief, and Economic Security (CARES) ActSection 18115,these changes went into effect on August 1st. But did anythingreallyhappen?\"), mdx(\"p\", null, \"As a follow up to the\", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://blog.civicdatadesignlab.mit.edu/data-from-reported-covid-19-tests-are-telling-an-incomplete-story:-here's-what-you-need-to-know\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"previous article\"), \"on missing reported race data in COVID-19 tests nationwide, we wanted to see the significant effects (if any) of the new federal guidance passed in the CARES Act Section 18115. Previously, we found large gaps in the aggregate data across the United States. From this, we asked if anything could be done at individual laboratories or medical testing centers to compensate for the gap. Now, we seek to investigate the impact of the new federal regulation on reporting race data.\"), mdx(\"p\", null, \"Data Comparisons, Before and After 18115\"), mdx(\"p\", null, \"Section 18115 may actually be impacting the level of reported race data nationwide\\u2026 But is it enough?\"), mdx(\"p\", null, \"From July 26th to August 26th, positive COVID-19 cases increased by over 1.5 million but only about 1 million had associated race data.\"), mdx(\"p\", null, \"In the United States, the percent of cases with associated race data has varied over time:\"), mdx(\"ol\", null, mdx(\"li\", {\n    parentName: \"ol\"\n  }, \"cumulative as of August 26th: 55.65%\"), mdx(\"li\", {\n    parentName: \"ol\"\n  }, \"only between July 26th and August 26th: 66.10%\"), mdx(\"li\", {\n    parentName: \"ol\"\n  }, \"cumulative as of July 26th: 51.75%\")), mdx(\"p\", null, \"[[\", \"insert bar graph]\", \"](\", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://chart-studio.plotly.com/~brianwilliams2022/17.embed\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"https://chart-studio.plotly.com/~brianwilliams2022/17.embed\"), \")\"), mdx(\"p\", null, \"This visualization shows the difference of percents of cases where race data is known, per state. The number represented in each bar is the percent difference in cases with associated race between two different periods: fromJuly 26th to August 26thand from the beginning of data collection up until July 26th.\"), mdx(\"p\", null, \"For example, let\\u2019s say that a given state\\u2019s total cases rose from July to August by x, and of those cases, there is a subsection where race data is unknown. Let\\u2019s say this subsection of unknown race data increases by y. I calculated 1 - (y/x), and compared that same calculation instead with the cumulative period from toward the beginning of the pandemic (late March) to July 26th.\"), mdx(\"p\", null, \"Some of these values are negative because the total number of Other and Unknown cases actuallyincreasesfrom July to August at a greater percentage compared to the beginning of the pandemic. This is pretty alarming.\"), mdx(\"p\", null, \"Please note that North Dakota (ND) seems to have a very large value: 87%. This is due to the fact that North Dakota only very recently started reporting race data foranyof their cases.\"), mdx(\"p\", null, \"But why?\"), mdx(\"p\", null, \"This seems unusual but I think it can be explained by retroactive revisions to the data (either by individual laboratories or a state\\u2019s Department of Public Health) which would move cases from these categories to their accurate racial category.\"), mdx(\"p\", null, \"For example, if a scientist was able to confirm a case or a set of cases belonged to certain demographic after the total number of cases had already been reported, you would simply move cases over to their respective categories. Maybe in certain situations, backlogs of case data prevent labs from sorting cases by demographic data before state deadlines but as time goes along, they are able to update their reported case data. This doesn\\u2019t seem to happen in many states and the testing efficiency problem could easily be a bigger and more widespread problem than I am expressing/speculating here.\"), mdx(\"p\", null, \"Here\\u2019s a regional breakdown of the same data.\"), mdx(\"p\", null, \"[[\", \"insert color map]\", \"](\", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"http://plotly.com/~brianwilliams2022/35.embed\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"http://plotly.com/~brianwilliams2022/35.embed\"), \")\"), mdx(\"p\", null, \"Discussion: Almost too little, too late\"), mdx(\"p\", null, \"So far, the national average of cases with race data increased by about 15% directly following the period Section 18115 went into effect, compared to reported race averages during the rest of the pandemic.\"), mdx(\"p\", null, \"Is this difference big enough? And how much of it can be directly attributed to Section 18115? To be quite honest\\u2026 I\\u2019m not sure.\"), mdx(\"p\", null, \"Though somewhat significant, the impact is almost too little too late. Just imagine what we\\u2019re not seeing, and the things we\\u2019ve \", \"*\", \"already\", \"*\", \" missed. Before August, there were more than 2 million Covid-19 tests that were unidentifiable by race. This type of federal guidance should have been in place since February and at the latest, the beginning of March.\"), mdx(\"p\", null, \"It doesn\\u2019t seem like we will have access to complete, accurate, and thorough data sets into the foreseeable future for many reasons starting at the laboratory level stretching all the way to the federal level. I just hope policymakers, publicly obligated to support our communities, are doing their best trying to walk in the dark during this pandemic.\"), mdx(\"p\", null, \"Sources\"), mdx(\"ol\", null, mdx(\"li\", {\n    parentName: \"ol\"\n  }, mdx(\"a\", _extends({\n    parentName: \"li\"\n  }, {\n    \"href\": \"https://www.hhs.gov/sites/default/files/covid-19-laboratory-data-reporting-guidance.pdf\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"https://www.hhs.gov/sites/default/files/covid-19-laboratory-data-reporting-guidance.pdf\")), mdx(\"li\", {\n    parentName: \"ol\"\n  }, mdx(\"a\", _extends({\n    parentName: \"li\"\n  }, {\n    \"href\": \"https://www.cdc.gov/coronavirus/2019-ncov/lab/reporting-lab-data.html#what-to-include\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"https://www.cdc.gov/coronavirus/2019-ncov/lab/reporting-lab-data.html#what-to-include\"))));\n}\n;\nMDXContent.isMDXComponent = 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","canonical_url":null,"subscription":true,"body":"function _extends() { _extends = Object.assign || function (target) { for (var i = 1; i < arguments.length; i++) { var source = arguments[i]; for (var key in source) { if (Object.prototype.hasOwnProperty.call(source, key)) { target[key] = source[key]; } } } return target; }; return _extends.apply(this, arguments); }\n\nfunction _objectWithoutProperties(source, excluded) { if (source == null) return {}; var target = _objectWithoutPropertiesLoose(source, excluded); var key, i; if (Object.getOwnPropertySymbols) { var sourceSymbolKeys = Object.getOwnPropertySymbols(source); for (i = 0; i < sourceSymbolKeys.length; i++) { key = sourceSymbolKeys[i]; if (excluded.indexOf(key) >= 0) continue; if (!Object.prototype.propertyIsEnumerable.call(source, key)) continue; target[key] = source[key]; } } return target; }\n\nfunction _objectWithoutPropertiesLoose(source, excluded) { if (source == null) return {}; var target = {}; var sourceKeys = Object.keys(source); var key, i; for (i = 0; i < sourceKeys.length; i++) { key = sourceKeys[i]; if (excluded.indexOf(key) >= 0) continue; target[key] = source[key]; } return target; }\n\n/* @jsx mdx */\nvar _frontmatter = {\n  \"title\": \"H2A: Seeing Sketchiness in Data\",\n  \"author\": \"Evan Denmark\",\n  \"date\": \"2020-08-22T00:00:00.000Z\",\n  \"excerpt\": \"In part two, we examine how the missing data associated with H2A hints at potentially nefarious behavior. \",\n  \"tags\": [\"Economy\", \"Data\"],\n  \"hero\": \"images/totalinstances.png\"\n};\n\nvar makeShortcode = function makeShortcode(name) {\n  return function MDXDefaultShortcode(props) {\n    console.warn(\"Component \" + name + \" was not imported, exported, or provided by MDXProvider as global scope\");\n    return mdx(\"div\", props);\n  };\n};\n\nvar layoutProps = {\n  _frontmatter: _frontmatter\n};\nvar MDXLayout = \"wrapper\";\nreturn function MDXContent(_ref) {\n  var components = _ref.components,\n      props = _objectWithoutProperties(_ref, [\"components\"]);\n\n  return mdx(MDXLayout, _extends({}, layoutProps, props, {\n    components: components,\n    mdxType: \"MDXLayout\"\n  }), mdx(\"p\", null, \"The H2A Visa program has become \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://blog.civicdatadesignlab.mit.edu/america's-essential-yet-unknown-program:-h2a\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"increasingly essential\"), \" to the American food supply chain. Since 2012, the number of participating farms, visa applications, worker hours, and total expense of the program have risen significantly. However, it hasn\\u2019t all been good. \"), mdx(\"p\", null, \"\\u201CWith the explosion in usage of the H2A program \\u2026 we\\u2019ve seen the abuse of the program grow,\\u201D said Caitlin Ryland, the Supervising Attorney at the Legal Aid of North Carolina, a nonprofit law firm dedicated to equal access to justice for low income workers.\"), mdx(\"p\", null, \"Farmers employing foreign workers through the H2A program must abide by strict \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://www.dol.gov/agencies/whd/agriculture\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"labor laws\"), \" to ensure that their workers are treated fairly and paid appropriately. However, \", mdx(\"a\", _extends({\n    parentName: \"p\"\n  }, {\n    \"href\": \"https://www.buzzfeednews.com/article/kenbensinger/the-pushovers\",\n    \"target\": \"_blank\",\n    \"rel\": \"noreferrer\"\n  }), \"recent reports\"), \" have shown the potential for worker abuse in the H2A program. Inspired by these multiple reports, we decided to investigate the data surrounding the violations in the H2A program.\"), mdx(\"p\", null, \"According to the US Department of Labor (DOL) Wage and Hour Division\\u2019s public data on enforcement, the number of federal H2A violations has dramatically increased in the past two decades. H2A violations may include improper housing requirements, poor working conditions, or improper payment of workers. The data displayed in the graph below shows the number of H2A violations since 2000. In this data, a list of farms that have violated H2A policy, the number of violations per investigation, and the duration of the violations are all provided.\"), mdx(\"p\", null, mdx(\"img\", _extends({\n    parentName: \"p\"\n  }, {\n    \"src\": \"https://lh6.googleusercontent.com/0ARiQGoswpnFFuxDilxkwkZzERn3aVo5136q60ljyl3PmjE3K2w6-Ur-3e2akwff0eHQmp7eQ80LNApi5MgIM4oDAHQ_I-o7ouPNSWJ-TYK-XG9A9jWJCbTM0nAvQgztjkdrep4y\",\n    \"alt\": null\n  })), mdx(\"em\", {\n    parentName: \"p\"\n  }, \"Data provided by the US Department of Labor Wage and Hour Division\\u2019s WHISARD data, updated in July 2020.\")), mdx(\"p\", null, \"This increase in violations comes from an increased reporting of violations in addition to a lack of government oversight of the program.\"), mdx(\"p\", null, \"\\u201CMost of \", \"[\", \"DOL\\u2019s] inspections are complaint driven,\\u201D says Ryland, which means that many farms may be committing H2A violations that are not represented in the data.\"), mdx(\"p\", null, \"Despite the growth of the program, the multiple agencies that enforce the H2A laws are significantly lacking. According to Ryland, the North Carolina Department of Labor has only \\u201Cfive or six inspectors for about two thousand labor camp sites.\\u201D\"), mdx(\"p\", null, \"To make matters even more complicated, Rylands believes that during COVID, they\\u2019re not \\u201Cdoing any onsite investigations.\\u201D\"), mdx(\"p\", null, \"Notably, the data displayed shows a significant decrease in violations in recent years. One possible reason is that it can take time to investigate and confirm a set of violations. Ryland said that workers \\u201Ctypically don\\u2019t learn about the results of their complaint for about a two year period,\\u201D which renders the visualization incomplete.\"), mdx(\"p\", null, \"The lack of government oversight also points to serious questions in the H2A application procedure. In addition to the violation enforcement data, the Department of Labor Employment and Training Administration also publishes the H2A visa applications of each farm. By combining these two datasets, there are some jarring artifacts.\"), mdx(\"p\", null, \"For example, Lewis M. Bailey IV Farms, a Mississippi potato grower, had a total of 180 accepted visa applications in early 2019 to work the fields until November. However, by the end of June, the DOL confirmed 178 violations on the Bailey Farm, resulting in over $325,000 in worker backwages (i.e. over 1 month of pay for 178 workers).\"), mdx(\"p\", null, \"Despite a violation of this magnitude, the DOL approved 230 H2A applications to the Bailey Farm for the August to November harvest on July 9 - only three weeks after the end of the major violation.\"), mdx(\"p\", null, \"Although the data cannot tell us the full story, it does point to potentially glaring missteps by the Department of Labor. The fact that a farm like Bailey Farm can be approved even after a large violation questions forces us to not only question the DOL\\u2019s application process but also to wonder how farms respond to violations. That is, after a violation, do farms respect the authority of the DOL?\"), mdx(\"p\", null, \"Of all of the farms who applied for H2A applications in 2019, 2.25% had previously violated H2A policy. With this in mind, we wondered if farms who had previously violated H2A policy tended to violate again. As shown in the below graph, we examined the recidivism - the tendency to reoffend - of farms who have broken H2A protocols at least three times in the last two decades.\"), mdx(\"p\", null, mdx(\"img\", _extends({\n    parentName: \"p\"\n  }, {\n    \"src\": \"https://lh4.googleusercontent.com/bqpd3z76Dk0tV2ZlocL9GYSUW_LcmuUu5b0g7mL5B2dQcbZkAst-QU2rqzPlGlwoKgwYXFdedXcZ2Fz2MDI3m8FYQ_JzSNTxCx23rMlM37b12y8dHCIHs-tjusoDfylKm3FZcp2l\",\n    \"alt\": null\n  }))), mdx(\"p\", null, \"From this data, those multi-violating offenders tended to not offend nearly as bad as before.\"), mdx(\"p\", null, \"In addition to potentially sketchy farms, some law firms (who are contracted by farms to apply for H2A visas) stick out as outliers when examining their rates of violation. For example, over 35% of the nearly 4,000 visas applied for by Farmer, Farmer, & Brown PLLC - a firm based out of Georgia - were contracted by farms who had previously violated H2A policy. Why is is that some law firms are associated with this sketchy behavior? \"), mdx(\"p\", null, \"As with many data projects, the data is only a single source and in order to understand the full story, deeper investigations must be done. However, these initial investigations show that data can hint at a larger behavior, including a lack of government oversight, a lack of violation reporting, and potentially nefarious behavior by both farms and law firms.\"), mdx(\"p\", null, \"What is evident, however, is the amount of missing data within this realm, and because of the magnitude of it, it can be difficult to grasp the scale of the worker abuse problem by the data alone.\"));\n}\n;\nMDXContent.isMDXComponent = 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