Tempe’s trust data for this measure is collected every month and comes from the “Safety” result from the monthly administered Police Sentiment Survey. There is one question which feeds into these results: "When it comes to the threat of crime, how safe do you feel in your neighborhood?" Benchmark data is from cohorts of communities with similar characteristics, such as size, population density, and region. This data is collected every month and quarter via a recurring report. This page provides data for the Feeling of Safety in Your Neighborhood performance measure. The performance measure dashboard is available at 1.05 Feeling of Safety in Your Neighborhood. Additional Information Source: Zencity Contact: Adam SamuelsContact email: Adam_Samuels@tempe.govData Source Type: Excel, CSVPreparation Method: Take the "Safety" score from the Police Sentiment Survey. This score includes the average of the top two results from the question underneath this area on the report. These months are then averaged to get the quarterly score.Publish Frequency: MonthlyPublish Method: Manual Data Dictionary

Recorded crime figures for CSP areas. Number of offences for the last two years, percentage change, and rates per 1,000 population for the latest year.

The Department of Justice launched Operation Weed and Seed in 1991 as a means of mobilizing a large and varied array of resources in a comprehensive, coordinated effort to control crime and drug problems and improve the quality of life in targeted high-crime neighborhoods. In the long term, Weed and Seed programs are intended to reduce levels of crime, violence, drug trafficking, and fear of crime, and to create new jobs, improve housing, enhance the quality of neighborhood life, and reduce alcohol and drug use. This baseline data collection effort is the initial step toward assessing the achievement of the long-term objectives. The evaluation was conducted using a quasi-experimental design, matching households in comparison neighborhoods with the Weed and Seed target neighborhoods. Comparison neighborhoods were chosen to match Weed and Seed target neighborhoods on the basis of crime rates, population demographics, housing characteristics, and size and density. Neighborhoods in eight sites were selected: Akron, OH, Bradenton (North Manatee), FL, Hartford, CT, Las Vegas, NV, Pittsburgh, PA, Salt Lake City, UT, Seattle, WA, and Shreveport, LA. The "neighborhood" in Hartford, CT, was actually a public housing development, which is part of the reason for the smaller number of interviews at this site. Baseline data collection tasks included the completion of in-person surveys with residents in the target and matched comparison neighborhoods, and the provision of guidance to the sites in the collection of important process data on a routine uniform basis. The survey questions can be broadly divided into these areas: (1) respondent demographics, (2) household size and income, (3) perceptions of the neighborhood, and (4) perceptions of city services. Questions addressed in the course of gathering the baseline data include: Are the target and comparison areas sufficiently well-matched that analytic contrasts between the areas over time are valid? Is there evidence that the survey measures are accurate and valid measures of the dependent variables of interest -- fear of crime, victimization, etc.? Are the sample sizes and response rates sufficient to provide ample statistical power for later analyses? Variables cover respondents' perceptions of the neighborhood, safety and observed security measures, police effectiveness, and city services, as well as their ratings of neighborhood crime, disorder, and other problems. Other items included respondents' experiences with victimization, calls/contacts with police and satisfaction with police response, and involvement in community meetings and events. Demographic information on respondents includes year of birth, gender, ethnicity, household income, and employment status.

The purpose of the study was to evaluate the effects of Neighborhood Watch signs on perceived crime rates, likelihood of victimization, community safety, and estimates of home and community quality. Part 1 (Study One Data) assessed the causal impact of Neighborhood Watch sign presence and content on perceptions of the community. Three Neighborhood Watch signs were incorporated into a series of slide show presentations. The signs utilized the traditional orange and white color scheme with black text and were used to represent an injunctive norm alone, a low descriptive norm for crime, or a high descriptive norm for crime. Digital color images of a for-sale home and the surrounding neighborhood of a middle class community in North San Diego County were shown to 180 undergraduates recruited from the Psychology Department's Human Participant Pool, and from other lower division general education courses at California State University, San Marcos, between July and November of 2005. Three of the slide shows were designated as Neighborhood Watch communities with one of the three sign types posted, and the fourth slide show served as a control with no posted crime prevention signs. Each slide show consisted of 20 images of the home and community, along with four instruction slides. Part 2 (Study Two Data) replicated the basic effect from Study 1 and extended the research to examine the moderating role of community social economic status (SES) on the effects of the Neighborhood Watch signs. Participants were 547 undergraduate students recruited from the Psychology Department's Human Participant Pool, and from other lower division general education courses at California State University and Palomar Community College in San Marcos, between January and September 2006. A total of 12 slide shows were utilized in Study Two, such that each of the four sign conditions from Study One was represented across each of the three communities (Low, Middle, and High SES). Part 3 (Study Three Data) examined the potential for the physical condition of the Neighborhood Watch signs posted in the community to convey normative information about the presence and acceptance of crime in the community. Participants were 364 undergraduate students recruited from the Psychology Department's Human Participant Pool, and from other lower division general education courses at California State University and Palomar Community College in San Marcos, between October 2006 and March 2007. Study Three used the same generic (Injunctive Norm, Program Only) sign that was utilized in Studies One and Two. However, three variations (new, aged, and defaced) of the sign were used. The surveys used for Study One, Study Two, and Study Three, were identical. The data include variables on perceived crime rates, perceived likelihood of victimization, perceived community safety, community ratings, self-protective behavior, burglar's perspective, manipulation check, and demographics of the respondent.

The Delta Neighborhood Physical Activity Study was an observational study designed to assess characteristics of neighborhood built environments associated with physical activity. It was an ancillary study to the Delta Healthy Sprouts Project and therefore included towns and neighborhoods in which Delta Healthy Sprouts participants resided. The 12 towns were located in the Lower Mississippi Delta region of Mississippi. Data were collected via electronic surveys between August 2016 and September 2017 using the Rural Active Living Assessment (RALA) tools and the Community Park Audit Tool (CPAT). Scale scores for the RALA Programs and Policies Assessment and the Town-Wide Assessment were computed using the scoring algorithms provided for these tools via SAS software programming. The Street Segment Assessment and CPAT do not have associated scoring algorithms and therefore no scores are provided for them. Because the towns were not randomly selected and the sample size is small, the data may not be generalizable to all rural towns in the Lower Mississippi Delta region of Mississippi. Dataset one contains data collected with the RALA Programs and Policies Assessment (PPA) tool. Dataset two contains data collected with the RALA Town-Wide Assessment (TWA) tool. Dataset three contains data collected with the RALA Street Segment Assessment (SSA) tool. Dataset four contains data collected with the Community Park Audit Tool (CPAT). [Note : title changed 9/4/2020 to reflect study name] Resources in this dataset:Resource Title: Dataset One RALA PPA Data Dictionary. File Name: RALA PPA Data Dictionary.csvResource Description: Data dictionary for dataset one collected using the RALA PPA tool.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset Two RALA TWA Data Dictionary. File Name: RALA TWA Data Dictionary.csvResource Description: Data dictionary for dataset two collected using the RALA TWA tool.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset Three RALA SSA Data Dictionary. File Name: RALA SSA Data Dictionary.csvResource Description: Data dictionary for dataset three collected using the RALA SSA tool.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset Four CPAT Data Dictionary. File Name: CPAT Data Dictionary.csvResource Description: Data dictionary for dataset four collected using the CPAT.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset One RALA PPA. File Name: RALA PPA Data.csvResource Description: Data collected using the RALA PPA tool.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset Two RALA TWA. File Name: RALA TWA Data.csvResource Description: Data collected using the RALA TWA tool.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset Three RALA SSA. File Name: RALA SSA Data.csvResource Description: Data collected using the RALA SSA tool.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset Four CPAT. File Name: CPAT Data.csvResource Description: Data collected using the CPAT.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Data Dictionary. File Name: DataDictionary_RALA_PPA_SSA_TWA_CPAT.csvResource Description: This is a combined data dictionary from each of the 4 dataset files in this set.

Police recorded crime figures by Police Force Area and Community Safety Partnership areas (which equate in the majority of instances, to local authorities).

This dataset tracks annual diversity score from 2019 to 2023 for Public Safety Academy School District vs. California

This data supports the 1.05 Feeling of Safety in Your Neighborhood and 2.06 Police Trust Score performance measures.This data is the result of a community survey of approximately 500 residents collected electronically and monthly by Zencity on behalf of Tempe Police Department. The scores are provided to TPD monthly in PDF form, and are then transferred to Excel for Open Data. The trust score is a 0 to 100 measure, and is a combination of two questions: How much do you agree with this statement? Trust-Respect: The police in my neighborhood treat people with respect. How much do you agree with this statement? Trust-Listen: The police in my neighborhood listen to and take into account the concerns of local residents.The safety score is a 0 to 100 measure, and scores residents' feelings of safety in their neighborhood.The performance measure pages are available at 1.05 Feeling of Safety in Your Neighborhood and 2.06 Police Trust Score.Additional InformationSource: ZencityContact (author): Carlena OroscoContact E-Mail (author): Carlena_Orosco@tempe.gov Contact (maintainer): Carlena OroscoContact E-Mail (maintainer): Carlena_Orosco@tempe.gov Data Source Type: Zencity REST APIPreparation Method: This data is from a citizen survey collected monthly by Zencity and provided in an automated survey feed to the City of Tempe.Publish Frequency: MonthlyPublish Method: Zencity REST API Automated Survey Feed Updates ArcGIS Online feature layer.Data Dictionary

Crime severity index (violent, non-violent, youth) and weighted clearance rates (violent, non-violent), Canada, provinces, territories and Census Metropolitan Areas, 1998 to 2023.

Comprehensive crime data for Toronto neighborhoods

This dataset tracks annual distribution of students across grade levels in Public Safety Academy School District and average distribution per school district in California

Toronto Neighbourhoods Boundary File includes Crime Data by Neighbourhood. Counts are available at the offence and/or victim level for Assault, Auto Theft, Bike Theft, Break and Enter, Robbery, Theft Over, Homicide, Shootings and Theft from Motor Vehicle. Data also includes crime rates per 100,000 people by neighbourhood based on each year's Projected Population by Environics Analytics.This data does not include occurrences that have been deemed unfounded. The definition of unfounded according to Statistics Canada is: “It has been determined through police investigation that the offence reported did not occur, nor was it attempted” (Statistics Canada, 2020).**The dataset is intended to provide communities with information regarding public safety and awareness. The data supplied to the Toronto Police Service by the reporting parties is preliminary and may not have been fully verified at the time of publishing the dataset. The location of crime occurrences have been deliberately offset to the nearest road intersection node to protect the privacy of parties involved in the occurrence. All location data must be considered as an approximate location of the occurrence and users are advised not to interpret any of these locations as related to a specific address or individual.NOTE: Due to the offset of occurrence location, the numbers by Division and Neighbourhood may not reflect the exact count of occurrences reported within these geographies. Therefore, the Toronto Police Service does not guarantee the accuracy, completeness, timeliness of the data and it should not be compared to any other source of crime data.By accessing these datasets, the user agrees to full acknowledgement of the Open Government Licence - Ontario..In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data. ** Statistics Canada. 2020. Uniform Crime Reporting Manual. Surveys and Statistical Programs. Canadian Centre for Justice Statistics.

Please see data table https://data.tempe.gov/datasets/tempegov::police-sentiment-survey-detail-1/about for continued data updates. This table was deprecated 11/3/2022.-----------------------------------------------This data supports the 1.05 Feeling of Safety in Your Neighborhood and 2.06 Police Trust Score performance measures.This data is the result of a community survey of approximately 500 residents collected electronically and monthly by Elucd on behalf of Tempe Police Department. The scores are provided to TPD monthly in PDF form, and are then transferred to Excel for Open Data. The trust score is a 0 to 100 measure, and is a combination of two questions: How much do you agree with this statement? The police in my neighborhood treat people with respect. How much do you agree with this statement? The police in my neighborhood listen to and take into account the concerns of local residents.The safety score is a 0 to 100 measure, and scores residents' feelings of safety in their neighborhood.The performance measure pages are available at 1.05 Feeling of Safety in Your Neighborhood and 2.06 Police Trust Score.Additional InformationSource: ElucdContact (author): Carlena OroscoContact E-Mail (author): Carlena_Orosco@tempe.gov Contact (maintainer): Carlena OroscoContact E-Mail (maintainer): Carlena_Orosco@tempe.gov Data Source Type: ExcelPreparation Method: This data is from a citizen survey collected monthly by Elucd and provided in Excel for publication.Publish Frequency: MonthlyPublish Method: ManualData Dictionary

ObjectiveGiven the limited information about how neighborhood environment relates to physical activity (PA) in Hispanic families, this work examined cross-sectional associations between perceived neighborhood environment and PA of Hispanic parents and children.MethodsParticipants were 137 Hispanic parent-child dyads (children aged 6–11 years) in South Phoenix, AZ, USA. Parents completed a survey about their own and their child's PA, and perceptions of neighborhood environment (i.e., scores of walking/cycling, neighborhood aesthetics, traffic safety, and crime rate) using NEWS survey. Participants also wore an accelerometer for 7 days.ResultsChildren engaged in 60 min of moderate-to-vigorous PA (MVPA) on 2.3, and parents in 30 min of MVPA on 2.1 days per weeks. Additionally, children engaged in 104.4 min, and parents in 65.3 min of accelerometer-assessed MVPA per day. Participants rated their neighborhood (range 0–4) as favorable regarding walking/cycling (mean score 3.1), aesthetics (2.4), traffic safety (2.5), and crime rate (3.1). In Spearman correlation analyses, better neighborhood aesthetics was associated with higher accelerometer-assessed MVPA in children (r = 0.25, p = 0.04). Multiple linear regression analyses revealed an association between traffic safety and parent-reported MVPA in children (standardized beta coefficient 0.19, p = 0.03). No further associations between scores of neighborhood environment and physical activity in either children or parents were observed.ConclusionOur findings may underscore the importance of neighborhood aesthetics and traffic safety for PA engagement in children. Longitudinal studies are needed to confirm our observations, and to untangle potential mechanisms linking neighborhood environment and PA in understudied populations such as Hispanics.

This dataset tracks annual diversity score from 2014 to 2023 for Detroit Public Safety Academy School District vs. Michigan

Historical Dataset of Public Safety Academy School District is provided by PublicSchoolReview and contain statistics on metrics:Comparison of Diversity Score Trends,Total Revenues Trends,Total Expenditure Trends,Average Revenue Per Student Trends,Average Expenditure Per Student Trends,Reading and Language Arts Proficiency Trends,Math Proficiency Trends,Overall School District Rank Trends,American Indian Student Percentage Comparison Over Years (2019-2022),Asian Student Percentage Comparison Over Years (2022-2023),Hispanic Student Percentage Comparison Over Years (2019-2023),Black Student Percentage Comparison Over Years (2019-2023),White Student Percentage Comparison Over Years (2019-2023),Two or More Races Student Percentage Comparison Over Years (2019-2023),Comparison of Students By Grade Trends

This is the most current information as of the date of upload. This provides the user the ability to view the most current crime information within Kansas City, Missouri. The displayed information is the most current information from the data source as of the date of upload. The data source is dynamic and therefore constantly changing. Changes to the information may occur, as incident information is refined. While the Board of Police Commissioners of Kansas City, Missouri (Board) makes every effort to maintain and distribute accurate information, no warranties and/or representations of any kind are made regarding information, data or services provided. The Board is not responsible for misinterpretation of this information and makes no inference or judgment as to the relative safety to any particular area or neighborhood. In no event shall the Board be liable in any way to the users of this data. Users of this data shall hold the Board harmless in all matters and accounts arising from the use and/or accuracy of this data.

Crime Severity Score (CSS) data for police force areas and community safety partnerships, which equate in the majority of instances to local authorities. Includes a data tool to enable production of summary charts on trends and comparisons between areas.

In 2024, Pietermaritzburg in South Africa ranked first in the crime index among African cities, scoring **** index points. The six most dangerous areas on the continent were South African cities. Furthermore, Pretoria and Johannesburg followed, with a score of **** and **** points, respectively. The index estimates the overall level of crime in a specific territory. According to the score, crime levels are classified as very high (over 80), high (60-80), moderate (40-60), low (20-40), and very low (below 20). Contact crimes are common in South Africa Contact crimes in South Africa include violent crimes such as murder, attempted murder, and sexual offenses, as well as common assault and robbery. In fiscal year 2022/2023, the suburb of Johannesburg Central in the Gauteng province of South Africa had the highest number of contact crime incidents. Common assault was the main contributing type of offense to the overall number of contact crimes. Household robberies peak in certain months In South Africa, June, July, and December experienced the highest number of household robberies in 2023. June and July are the months that provide the most hours of darkness, thus allowing criminals more time to break in and enter homes without being detected easily. In December, most South Africans decide to go away on holiday, leaving their homes at risk for a potential break-in. On the other hand, only around ** percent of households affected by robbery reported it to the police in the fiscal year 2022/2023.