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Case Closing without a New Offense CY 2018 By County as Reported by the Juvenile Court Judges' Commission
data.pa.gov | Last Updated 2022-10-17T20:21:58.000ZThe juvenile justice system has a responsibility to protect the community from known juvenile offenders. Juveniles who do not commit a new offense while under court supervision have a higher probability of remaining crime free. This data represents the number and percentage of juveniles who successfully completed supervision without a new offense resulting in a Consent Decree, Adjudication of Delinquency, ARD, Nolo Contendere, or finding of guilt in a criminal procedure. <br/> CY - Calendar Year This dataset is contained within the Juvenile Court Judges' Commission’s 2018 Statewide Juvenile Justice Outcome Measure report: this report reflects outcomes of juvenile offenders whose cases were closed during the report period and who have received a period of supervision from a county juvenile probation department. These reported outcomes are associated with community protection, accountability, and competency development; three core goals of Pennsylvania's juvenile justice system. Since 2009, county juvenile probation departments have supervised and closed 126,006 cases. The proportion of cases closed successfully (without a new offense) during this time is 84.1%. For the year 2018, the proportion of cases closed successfully was 85.4%.
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Uninsured Population Census Data 1-year estimates 2017-Current Statewide Human Services and Insurance
data.pa.gov | Last Updated 2022-02-21T19:25:46.000ZThe American Community Survey (ACS) helps local officials, community leaders, and businesses understand the changes taking place in their communities. It is the premier source for detailed population and housing information about our nation. This dataset provides estimates for Health Insurance Coverage in Pennsylvania and is summarized from summary table S2701: SELECTED CHARACTERISTICS OF HEALTH INSURANCE COVERAGE IN THE UNITED STATES. A blank cell within the dataset indicates that either no sample observations or too few sample observations were available to compute the statistic for that area. Margin of error (MOE). Some ACS products provide an MOE instead of confidence intervals. An MOE is the difference between an estimate and its upper or lower confidence bounds. Confidence bounds can be created by adding the margin of error to the estimate (for the upper bound) and subtracting the margin of error from the estimate (for the lower bound). All published ACS margins of error are based on a 90-percent confidence level. While an ACS 1-year estimate includes information collected over a 12-month period, an ACS 5-year estimate includes data collected over a 60-month period. In the case of ACS 1-year estimates, the period is the calendar year (e.g., the 2015 ACS covers the period from January 2015 through December 2015).
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Uninsured Population Census Data 5-year estimates for release years 2017-Current County Human Services and Insurance
data.pa.gov | Last Updated 2022-02-21T19:25:39.000ZThe American Community Survey (ACS) helps local officials, community leaders, and businesses understand the changes taking place in their communities. It is the premier source for detailed population and housing information about our nation. This dataset provides estimates by county for Health Insurance Coverage and is summarized from summary table S2701: SELECTED CHARACTERISTICS OF HEALTH INSURANCE COVERAGE IN THE UNITED STATES. The 5-year estimates are used to provide detail on every county in Pennsylvania and includes breakouts by Age, Gender, Race, Ethnicity, Household Income, and the Ratio of Income to Poverty. An blank cell within the dataset indicates that either no sample observations or too few sample observations were available to compute the statistic for that area. Margin of error (MOE). Some ACS products provide an MOE instead of confidence intervals. An MOE is the difference between an estimate and its upper or lower confidence bounds. Confidence bounds can be created by adding the margin of error to the estimate (for the upper bound) and subtracting the margin of error from the estimate (for the lower bound). All published ACS margins of error are based on a 90-percent confidence level. While an ACS 1-year estimate includes information collected over a 12-month period, an ACS 5-year estimate includes data collected over a 60-month period. In the case of ACS 1-year estimates, the period is the calendar year (e.g., the 2015 ACS covers the period from January 2015 through December 2015). In the case of ACS multiyear estimates, the period is 5 calendar years (e.g., the 2011–2015 ACS estimates cover the period from January 2011 through December 2015). Therefore, ACS estimates based on data collected from 2011–2015 should not be labeled “2013,” even though that is the midpoint of the 5-year period. Multiyear estimates should be labeled to indicate clearly the full period of time (e.g., “The child poverty rate in 2011–2015 was X percent.”). They do not describe any specific day, month, or year within that time period.
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Workforce Innovation Opportunity Act (WIOA) Title III Performance Accountability Metrics PY 2017-2018 - Current Annual Labor and Industry
data.pa.gov | Last Updated 2022-06-09T15:50:25.000ZA comprehensive collection of data that assesses the effectiveness of Pennsylvania in achieving positive outcomes for individuals served by the workforce development system’s Title III Wagner-Peyser (Labor Exchange) program. Data is compiled in compliance with US Department of Labor’s Employment and Training Administration guidance on Workforce Innovation and Opportunity Act (WIOA) Performance Accountability. Data is available for the state and each of the CareerLink® offices in the commonwealth.
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Uninsured Population Census Data CY 2009-2014 Human Services
data.pa.gov | Last Updated 2022-10-18T14:19:11.000ZThis data is pulled from the U.S. Census website. This data is for years Calendar Years 2009-2014. Product: SAHIE File Layout Overview Small Area Health Insurance Estimates Program - SAHIE Filenames: SAHIE Text and SAHIE CSV files 2009 – 2014 Source: Small Area Health Insurance Estimates Program, U.S. Census Bureau. Internet Release Date: May 2016 Description: Model‐based Small Area Health Insurance Estimates (SAHIE) for Counties and States File Layout and Definitions The Small Area Health Insurance Estimates (SAHIE) program was created to develop model-based estimates of health insurance coverage for counties and states. This program builds on the work of the Small Area Income and Poverty Estimates (SAIPE) program. SAHIE is only source of single-year health insurance coverage estimates for all U.S. counties. For 2008-2014, SAHIE publishes STATE and COUNTY estimates of population with and without health insurance coverage, along with measures of uncertainty, for the full cross-classification of: •5 age categories: 0-64, 18-64, 21-64, 40-64, and 50-64 •3 sex categories: both sexes, male, and female •6 income categories: all incomes, as well as income-to-poverty ratio (IPR) categories 0-138%, 0-200%, 0-250%, 0-400%, and 138-400% of the poverty threshold •4 races/ethnicities (for states only): all races/ethnicities, White not Hispanic, Black not Hispanic, and Hispanic (any race). In addition, estimates for age category 0-18 by the income categories listed above are published. Each year’s estimates are adjusted so that, before rounding, the county estimates sum to their respective state totals and for key demographics the state estimates sum to the national ACS numbers insured and uninsured. This program is partially funded by the Centers for Disease Control and Prevention's (CDC), National Breast and Cervical Cancer Early Detection ProgramLink to a non-federal Web site (NBCCEDP). The CDC have a congressional mandate to provide screening services for breast and cervical cancer to low-income, uninsured, and underserved women through the NBCCEDP. Most state NBCCEDP programs define low-income as 200 or 250 percent of the poverty threshold. Also included are IPR categories relevant to the Affordable Care Act (ACA). In 2014, the ACA will help families gain access to health care by allowing Medicaid to cover families with incomes less than or equal to 138 percent of the poverty line. Families with incomes above the level needed to qualify for Medicaid, but less than or equal to 400 percent of the poverty line can receive tax credits that will help them pay for health coverage in the new health insurance exchanges. We welcome your feedback as we continue to research and improve our estimation methods. The SAHIE program's age model methodology and estimates have undergone internal U.S. Census Bureau review as well as external review. See the SAHIE Methodological Review page for more details and a summary of the comments and our response. The SAHIE program models health insurance coverage by combining survey data from several sources, including: •The American Community Survey (ACS) •Demographic population estimates •Aggregated federal tax returns •Participation records for the Supplemental Nutrition Assistance Program (SNAP), formerly known as the Food Stamp program •County Business Patterns •Medicaid •Children's Health Insurance Program (CHIP) participation records •Census 2010 Margin of error (MOE). Some ACS products provide an MOE instead of confidence intervals. An MOE is the difference between an estimate and its upper or lower confidence bounds. Confidence bounds can be created by adding the margin of error to the estimate (for the upper bound) and subtracting the margin of error from the estimate (for the lower bound). All published ACS margins of error are based on a 90-percent confidence level.
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Dangerous Dogs 1996-Current County Agriculture
data.pa.gov | Last Updated 2020-02-27T14:35:08.000ZHistorical results of Dangerous Dogs in Pennsylvania. A dangerous dog is one that has: (1) Inflicted severe injury on a human being without provocation on public or private property. (2) Killed or inflicted severe injury on a domestic animal, dog or cat without provocation while off the owner’s property. (3) Attacked a human being without provocation. (4) Been used in the commission of a crime. And the dog has either or both of the following: (1) A history of attacking human beings and/or domestic animals, dogs or cats without provocation. (2) A propensity to attack human beings and/or domestic animals, dogs or cats without provocation. *A propensity to attack may be proven by a single incident. Severe injury is defined as, [3 P.S. § 459-102] “Any physical injury that results in broken bones or disfiguring lacerations requiring multiple sutures or cosmetic surgery.” More information can be found here - https://www.agriculture.pa.gov/Animals/DogLaw/Dangerous%20Dogs/Pages/default.aspx More information on Chapter 27 Regulations - https://www.agriculture.pa.gov/Animals/DogLaw/Dangerous%20Dogs/Documents/Chapter%2027%20Dangerous%20Dogs.pdf PDF's for Chapter 27 and Pennsylvania Dog Laws are attached to the metadata
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Drug and Alcohol Treatment Get Help Now Intake Hotline November 2016 - Current Statewide Drug and Alcohol Programs
data.pa.gov | Last Updated 2023-09-19T14:35:29.000ZThis dataset reports statewide and county numbers of calls and intakes by individuals seeking treatment from hotline staff since the inception of Pennsylvania’s Get Help Now Hotline, text line, and chat line in November 2016. When a field is blank the information is not available; these data were not collected at the time of the phone call.
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Governor's Executive Budget Program Measures SFY 2017 - Current Annual Statewide Community and Economic Development
data.pa.gov | Last Updated 2023-03-22T21:40:57.000ZThe information included in this dataset is for the Governor’s Executive Budget and provides key Program Measures by Agency or Office.
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COVID-19 Aggregate Hospitalizations Current Weekly County Health NO FURTHER UPDATES
data.pa.gov | Last Updated 2024-05-08T14:27:07.000ZWeekly updates have finished with the June 28th update. “Note: Beginning 7/13/2022, the hospitals are no longer reporting data on airborne isolation beds resulting in null values being displayed for the airborne isolation bed metrics.” This dataset contains aggregate hospitalization data related to COVID-19 patient which includes availability of ICU beds, patients on ventilators, ventilators in use, and total patients hospitalized data at the state and county level for Pennsylvania residents. Data will be updated between 11:30 am to 1:30pm each Wednesday.
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Delinquency Dispositions CY 2014 - Current By County as Reported by the Juvenile Court Judges' Commission
data.pa.gov | Last Updated 2022-10-17T20:12:49.000ZThis dataset represents the total number of delinquency dispositions processed by Pennsylvania juvenile courts in 2018. A disposition is defined as an allegation of delinquency disposed of by the juvenile probation department and/or the court. This dataset is contained within the Juvenile Court Judges' Commission’s Calendar Year (CY) 2018 Juvenile Court Annual Report; this report provides an overview of Pennsylvania juvenile court statistics, during 2018, to measure and quantify work across the state by juvenile justice professionals. In Pennsylvania, juvenile court jurisdiction extends over individuals who have been alleged to have committed a delinquent act, as defined by 42. Pa. C. S. § 6301 et seq., on or after their tenth birthday and prior to reaching eighteen years of age. Juvenile court supervision can extend until the individual is twenty-one years of age if the individual is currently under supervision. Age for purposes of this section was calculated from the juvenile’s date of birth to the date of the offense in the written allegation. Any one youth may be involved in a number of dispositions within a calendar year containing multiple allegations. There were 22,023 delinquency dispositions in Pennsylvania during 2018. This represents a 1.3% decrease from 2017 and a 13.4% decrease since 2014. Allegheny County reported a decrease of 17.0% from 2017 to 2018, and Philadelphia County reported a 5.9% decrease for this time period. One-third of the total dispositions occurred in the four jurisdictions reporting more than 1,000 dispositions; these jurisdictions include Philadelphia, Allegheny, York, and Delaware.