This MANUFACTUREDDISORDERreadme.txt file was generated on 2022-04-07 by Kasey Henricks ------------------- GENERAL INFORMATION ------------------- 1. Title of Dataset Manufactured Disorder: Race, Policing, and Erroneous Ticketing in Chicago 2. Author Information Principal Investigator Contact Information Name: Kasey Henricks Institution: University of Tennessee at Knoxville and Kulturwissenschaftliches Institut Essen Address: 1115 Volunteer Blvd., 901 McClung Tower; Knoxville, TN Email: henricks@utk.edu 3. Date of data collection (single date, range, approximate date) 2017-08 through 2021-11 4. Geographic location of data collection (where was data collected?): Chicago, Illinois 5. Information about funding sources that supported the collection of the data: Russell Sage Foundation, Grant # 2105-32138 6. Abstract/description of the dataset: “Manufactured Disorder” is a case study of Chicago that focuses on parking tickets written under false pretenses. Multiple sources of administrative data are leveraged against one another to identify more than one in eight tickets over a six-year span were written under conditions when restrictions did not apply. The dataset reviews 3,590,005 tickets issued between August 1, 2012 and May 18, 2018, narrowing its attention to seven different types of parking restrictions that specify circumstantial conditions of compliance. These seven types of tickets were purposefully selected on the basis that their validity could be corroborated (or contested) by data routinely maintained by the City of Chicago (e.g., street cleaning schedules, residential parking zone, special event permits, etc.). The data are hierarchal insofar as they contain units of measure at the ticket-, issuing officer-, and tract- levels, although the data structure follows a partially crossed orientation (i.e., tickets are nested in officer- and tract- level units, but ticketing patterns of issuing officers are not restricted by neighborhood). 7: Keywords for the dataset (provide 3 - 5): data and society, parking tickets, race and ethnicity, policing, Chicago -------------------------- SHARING/ACCESS INFORMATION -------------------------- 1. Licenses/restrictions placed on the data: With proper attribution, the dataset is open access for unlimited sharing, access, and re-use. 2. Links to publications that cite or use the data: Henricks, Kasey and Ruben Ortiz. 2022. “The Irrelevance of Innocence: Ethnoracial Context, Occupational Differences in Policing, and Tickets Issued in Error.” Socius 8:doi: 10.1177/23780231221084774. Henricks, Kasey, Chris D. Poulos, Iván Arenas, Ruben Ortiz, and Amanda E. Lewis. 2022. 475,106 Mistakes: When Tickets are Issued under False Pretenses. Institute for Research on Race & Public Policy. 3. Links to other publicly accessible locations of the data: N/a 4. Links/relationships to ancillary data sets: See the word document file titled "Overview." 5. Was data derived from another source? If yes, list source(s): Yes, see the word document file titled "Overview." 6. Recommended citation for the data: Henricks, Kasey. 2022. Manufactured Disorder: Race, Policing, and Tickets Issued in Error. Tennessee Research and Creative Exchange: University of Tennessee. --------------------- DATA & FILE OVERVIEW --------------------- 1. File List A. Filename: overview.docx Short description: A document summarizes the data, method, and corresponding files of the dataset. B. Filename: all_tickets.sav Short description: A file that synthesizes all new and secondary data that comprise the dataset. C. Filename: script.R Short description: A computational script to replicate all findings in R for the article titled “The Irrelevance of Innocence: Ethnoracial Context, Occupational Differences in Policing, and Tickets Issued in Error.” D. Filename: errorByCA.csv Short description: A spreadsheet of the variables from the master data file but aggregated to Chicago’s 77 community areas. This file empirically anchors the report titled "475,106 Mistakes: When Tickets are Issued under False Pretenses." E. Filename: streetCleaningScheduleAllYears.xlsx Short description: A spreadsheet that outlines the street cleaning schedule for Chicago's ward-sections from 2012 to 2018. F. Filenames: streetSweeping2012.shp streetSweeping2013.shp streetSweeping2014.shp streetSweeping2015a.shp streetSweeping2015b.shp streetSweeping2016.shp streetSweeping2017.shp streetSweeping2018.shp Short description: Shapefiles that outline the borders of Chicago's ward-sections from 2012 to 2018. G. Filename: eventPermits.csv Short description: A spreadsheet that lists all special events registered between 2012 and 2018. H. Filename: winterOvernightParkingRestrictions.shp Short description: A shapefile that features the street networks of Chicago's 3-7am winter ban between 2012 and 2018. I. Filename: snowParkingRestrict2inch.shp Short description: A shapefile that features the street networks of Chicago's 2" snow route ban between 2012 and 2018. J. Filename: snowEvents.xlsx Short description: A spreadsheet of recorded snow events between 2012 and 2018. K. Filename: residentialZones.csv Short description: A spreadsheet that documents all the restricted residential zones between 2012 and 2018. L. Filename: communityAreas.shp Short description: A shapefile of Chicago's 77 community areas. M. Filename: centralBusinessDistrict.shp Short description: A shapefile of Chicago's Central Business District. N. Filename: centralBusinessDistrict.shp Short description: A shapefile of the Chicago Transit Authority's 10,895 bus stops, current as of 2019. O. Filename: hospitals.xlsx Short description: A spreadsheet that features the name and address of all 30 general hospitals in Chicago between 2012 and 2018. P. Filename: cpsSchools.xlsx Short description: A spreadsheet that features the name and address of all 751 schools in the Chicago Public Schools district between 2012 and 2018. 2. Relationship between files: See the word document file titled "Overview." 3. Additional related data collected that was not included in the current data package: Case-level parking tickets that serve as the basis for my inquiry derive from a dataset developed by ProPublica Illinois, in collaboration with WBEZ, titled “City of Chicago Parking and Camera Ticket Data.” Upon agreeing to the terms of use, the 6.26 GB file is available for public download at the following URL: https://www.propublica.org/datastore/dataset/chicago-parking-ticket-data. The file provides information on all vehicle noncompliance violations cited by the City of Chicago from January 1, 1996 to May 14, 2018. Included in this dataset are also camera-assisted tickets (e.g., red-light, speed-trap cameras) issued from November 1, 2003 to May 3, 2018. Altogether, these amount to 28,272,580 tickets. Each case features details on when, where, and by whom tickets were written, vehicle make, registration zip code, the ordinance violated, the payment status, and more. Data are current as of May 2018. 4. Are there multiple versions of the dataset? yes/no no -------------------------- METHODOLOGICAL INFORMATION -------------------------- 1. Description of methods used for collection/generation of data: See the word document file titled "Overview." 2. Methods for processing the data: See the word document file titled "Overview." 3. Instrument- or software-specific information needed to interpret the data: See the word document file titled "Overview." 4. Standards and calibration information, if appropriate: See the word document file titled "Overview." 5. Environmental/experimental conditions: n/a 6. Describe any quality-assurance procedures performed on the data: See the word document file titled "Overview." 7. People involved with sample collection, processing, analysis and/or submission: See the word document file titled "Overview." ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: [FILENAME] ----------------------------------------- 1. Number of variables: 37 2. Number of cases/rows: 3,590,005 3. Variable List A. Name: • id • wrongful • cpd_dummy • cbd_distance • bus_stop • hospital_distance • school_distance • bad_apple_all_tickets • percentBlack • percentLatinx • percentWhite • medInc • renter • popDensity • hhsWCar • lakefront • lag_all_tickets • year • violation_code • violation_description • officer • street_cleaning • residential_parking • downtown • winter_parking • special_events • tract • geoid10 • lag_winter_parking • lag_special_events • lag_resdiential_parking • lag_downtown • bad_apple_downtown • bad_apple_residential_parking • bad_apple_special_events • bad_apple_street_cleaning • bad_apple_winter_parking 4. Missing data codes: . 5. Specialized formats of other abbreviations used See the word document file titled "Overview."