Adult correctional services, operating expenditures for provincial, territorial and federal programs, provinces, territories and federal jurisdiction, five years of data.

This dataset contains survey data for the publication "The Invisible Women: The Costs of Prison and the Indirect Effects on Women" (Related publication only available in Spanish). The study seeks to draw attention to the families of people who are detained in the local Mexican prison system. The results of this study are divided into two parts: the first part shows the socio-demographic characteristics of those who visit the Centers for Social Rehabilitation including information about their education, work, and economic status, among others. The second part provides quantitative information on the economic, social and health costs that are imposed by a criminal model that fails to recognize its existence, and by a prison system that frequently fails to comply with the obligation to pay the expenses of those that have been put in seclusion.

This page details the data sources and methodology used in the 2023 report by Avery Fairburn, “Examining Jail Data in Hamilton County, TN”. Interactive data visualizations for the report can be found here. A data dictionary is provided in the file section.

Silverdale Detention Center Booking Records

This dataset was collected using a web scraper tool created by Wren Tefft, and the records included in the sample are from August 2nd, 2022 through January 31st, 2023. This data is still being collected daily. The scraper pulls the name, home address, age, charges, and arresting agency for each person booked into the jail. In the file available for download on this page, I have removed the names and street addresses of arrested individuals to maintain their privacy, but have included the city, state, and ZIP code.

Addresses

The addresses in these records are provided by arrestees upon being booked, and recorded by jail staff. The raw data contained a considerable number of errors, so I tested the validity of addresses by using Google’s Address Validation API, and categorized them based on the results:

Address Status - Valid w/ No Errors: Address was able to be identified by the Google API and confirmed as a known address of record with USPS, and included no errors. Non-address values (such as “Homeless”) that had no errors are included in this category as well. - Valid w/ Errors: Address was confirmed but included errors (such as a misspelled street name or city name, or an incorrect ZIP code). Non-address values (such as “Homeless”) that contained errors are included in this category as well. - Invalid: Address was not able to be confirmed, due to either too many errors, missing address components, or non-existent address components (such as a street number that did not correspond with any real location). - No Apt. Number: Address was confirmed, but is invalid due to a missing unit number. These addresses are included in analysis, as the street address is correct, but otherwise considered invalid as they are undeliverable. - None: No address or other value was listed by jail staff.

I also categorized addresses by type, to account for the fact that a large number of arrestees were listed as homeless, living at a hotel or homeless shelter, or living at a commercial address. Categories are detailed below:

Address Type - Single-Unit Residential: Valid residential addresses that do not contain a unit number. - Multi-Unit Residential Residential addresses that contain (or should contain) a unit number. Addresses that were missing a unit number are included in this category. - Commercial: Valid non-residential addresses not listed in another category. - Hotel: Valid addresses of hotels. - Community Kitchen: The address of a homeless service provider in Chattanooga, listed as the home address for a significant portion of arrestees. - Homeless: Arrestees that had “Homeless”, “Transient”, or variations listed instead of an address. - P.O. Box: P.O. boxes that were listed as home addresses. - Invalid: Addresses that were not able to be confirmed, due to either too many errors, missing address components, or non-existent address components (such as a street number that did not correspond with any real location). - None: No address or other value was listed by jail staff.

Primary Charges

To choose the primary charge in arrests that included multiple different charges, I used this method: Charges were ranked first by classification, from highest (Class A felony) to lowest (Class C misdemeanor). Out of a group of multiple charges, the primary charge would be the one with the highest classification. If there were multiple charges with the same classification (e.g. two class A misdemeanor charges), then the one listed first in the booking record was identified as the primary charge.

I made exceptions to this method for Violation of Probation, Failure to Appear charges, and Resisting or Evading Arrest charges, which I did not list as the primary charge except when there were no other charges. This was to account for the fact that Failure to Appear charges are typically issued as warrants, and the fact that being charged with another crime while on probation typically constitutes a probation violation.

There was also a group of charges that I did not list as primary unless they were the sole charge, due to the fact that their classification or definition is dependent on other charges. These charges were Possession of Firearm During a Felony, Contributing to the Deli...