Stepping Stones

Kindergarteners At or Above Reading Levels

Virginia screens all incoming kindergartners with a Phonological Awareness Literacy Screening (PALS) tool to understand children’s knowledge of important literacy fundamentals and to identify students who are at risk for reading difficulties. Early intervention is one mechanism to identify and combat disparities from widening as students enter kindergarten. In addition, PALS benchmark scores guide the state’s allocation of Early Intervention Reading Initiative funds.

• Data considerations: Administered to all incoming public school kindergartners, PALS-K scores can be used to provide a full picture of the incoming class. However, this measure provides no information on children not enrolled in public schools (e.g., children who are homeschooled or attend private schools).
• How is this measured?: This measure represents the number of incoming kindergarten students who are at or above PALS benchmarks as a percent of all incoming kindergarten students screened.

Standards of Learning

The Virginia Department of Education’s Standards of Learning (SOL) outline minimum expectations of what students should know and be able to do at each grade level in a range of subjects. SOL tests are administered in all Virginia public schools starting in 3rd grade, and the resulting pass rates are used to assess student achievement, evaluate school and district performance, and determine whether schools are meeting state and federal standards. Student performance is graded on a scale of 0-600 with 400-499 representing pass proficiency and 500 and above representing advanced proficiency.

The Virginia Board of Education revised both math and reading SOLs to raise standards and implemented these in the math SOL tests in 2012 and the reading SOL tests in 2013. Mirroring the trend in the state as a whole, both Charlottesville and Albemarle divisions saw a notable decline in pass rates for reading and math across 3rd, 5th, and 8th grade in the years these changes were implemented.

• Data considerations: Because SOL tests are administered to all children enrolled in public schools in Virginia, these data provide a full picture of the population of children in public schools; however, this measure provides no information on children not enrolled in public schools (e.g., children who are homeschooled or attend private schools). Further, SOL tests were not administered at the end of the 2019-2020 school year due to closures during the COVID-19 pandemic. While traditionally participation on the SOL tests has been high (approximately 95%), participation dropped notably in 2020-2021 (approximately 70%) as schools reopened with COVID health precautions.
• How is this measured?: The pass rate is the number of students in a given grade who passed the math or reading SOL test (i.e., scoring 400 or above) for that grade level as a percent of the total number of students in that grade who took the math or reading SOL test.

Math: Grades 3, 5, and 8

Math is a fundamental subject that is necessary for success in many college and career paths, and children who are proficient at math will be able to access a wide range of paths.

Reading: Grades 3, 5, and 8

Reading test scores measure a students’ ability to read at grade level. Not meeting reading proficiency has lasting impacts on student academic success, degree attainment, and future earnings. Third grade reading is particularly important as this is when children transition from learning to read to reading to learn.

Students Eligible for Special Education Services

Special education services are intended to ensure students with disabilities have access to a meaningful public education. The Individuals with Disability Education Act (IDEA) guarantees a free appropriate public education to all eligible children with documented disabilities. Students with a disability – hearing impairment, including deafness; speech or language impairment; visual impairment, including blindness; orthopedic impairment; autism; traumatic brain injury; developmental delay; other health impairment; intellectual disability; specific learning disability; serious emotional disturbance; or multiple disabilities – receive special education and related services outlined in an Individual Education Program (IEP) or other service plan. See VDOE for more details.

• Data considerations: These data are collected for the administration of special education services and represent the record of children deemed eligible for special education services. Eligibility is determined through evaluation processes to identify disabilities and determine needed services. Increasing numbers of students receiving special education services can reflect increased access to needed resources, as disability diagnoses become less stigmatized.
• How is this measured?: This metric is the number of students identified as eligible for special education services as a percent of all students in the school division.

English Learners

An English Learner (EL) is a student who is not fully proficient in English and requires language-based accommodations to effectively learn during their K-12 education. Multilingual learners have been a growing segment of the student population in Virginia but have not always had access to needed resources.

• Data considerations: An English Language Screening assessment is administered to potential EL students during the enrollment process and to all current EL students annually to determine eligibility for English language instructional services. The data can be used to provide a full picture of the current composition of EL students in schools. However, this measure provides no information on children not enrolled in public schools (e.g., children who are homeschooled or attend private schools).
• How is this measured?: The count of identified students who speak English as a second or other language and are emergent in the speaking, reading, writing, and/or understanding of English as a percent of all students in the school division. Former English Learners are not included in the count.

Average Daily Attendance

High Average Daily Attendance (ADA) indicates that students are attending school regularly, and regular attendance is associated with greater student success. Consequently, attendance and engagement have been a focus for educators and schools.

• Data considerations: This metric is derived from data collected as part of the administration of schools and provides a complete description of school attendance to the extent attendance data is recorded consistently and correctly within the schools that make up the division. However, Average Daily Attendance can mask chronic absenteeism as this metric does not incorporate information on who is absent. The same rate of Average Daily Attendance could result from most students missing a few days or from the same group of students missing many days.
• How is this measured?: ADA is calculated as the sum of daily attendance (children in school) as a percent of the sum of daily membership (children enrolled). It represents the percentage of a school’s student body in attendance on a typical day.

On-Time Graduation Rates

On-time graduation measures the percentage of students that graduated from public schools within four years of entering high school. On-time graduation is an important indicator of whether localities are preparing most students for college or career readiness, as a high school diploma is a standard requirement for many jobs and for accessing higher education.

• Data considerations: This rate is derived from Virginia’s longitudinal student data system linking the records of students who entered 9th grade for the first time in a given year (beginning in 2004) with their records four years later to determine their graduation or completion status. The measure accounts for student mobility, retention, and promotion patterns and provides a complete description of completion outcomes for each cohort attending public schools. Students who earn a GED or a certificate of completion are not counted as dropouts or as graduates when calculating the on-time graduation rate.
• How is this measured?: On-time graduation is defined as students who earn a Virginia Board of Education-approved diploma among students who entered 9th grade for the first time together and were scheduled to graduate four years later; the percent represents students in a cohort who graduated on time over all students in that cohort, (multiplied by 100). This measure recognizes that some students with disabilities and limited English proficiency are allowed more than the standard four years to earn a diploma and counts those students as “on-time” graduates. See VDOE for more.

Post-Secondary Enrollment

The rate of post-secondary enrollment measures the percent of graduating high school seniors who enter a higher education institution (e.g., college, university or community college) within 16 months after graduating from high school. It is increasingly common for jobs to require post-secondary education or postsecondary training or certification.

• Data considerations: This metric tracks each graduating cohort’s enrollment in a two- or four-year college or university anywhere in the United States. It is an accurate and complete reflection of education enrollment immediately following high school, but it does not include information on students who begin college more than 16 months after graduation.
• How is this measured?: The VDOE uses data from the National Student Clearinghouse to track college attendance nationwide among students graduating from Virginia’s public schools. This metric represents the number of students in a division’s graduating cohort who enroll in any institution of higher education within 16 months of graduating as a percent of the number of students in the graduating cohort.

High School Degree Attainment

Earning a high school (H.S.) diploma is a minimum requirement for many jobs and to pursue higher education, thus it can have wide-ranging health, social, and economic impacts. The rate of education attainment in a community not only reflects benefits to individuals but is also related to community economic and population health.

• Data considerations: This metric is derived from the American Community Survey (ACS), a continuous survey given to a sample of housing unit addresses each month. Each year the survey releases 5-year estimates, pooling data from all surveyed households throughout a 60-month period. As a survey, rather than a census, the ACS provides estimates of population characteristics and these estimates have a degree of uncertainty, or sampling error, associated with them. Importantly, this metric does not capture the performance of schools in a given city but rather on the highest level of education achieved by adults who reside in that city, regardless of where they attended school.
• How is this measured?: The measure is the count of residents who are 25 or over who have received at least a H.S. diploma or equivalent (including GEDs) over the count of all residents aged 25 or over in the relevant city, county, or state (multiplied by 100).

Registered Voters

Voting in elections is a central form of participation in a democracy. Until 2022, citizens in Virginia had to be registered voters prior to an election to participate–beginning in 2022, citizens could register the day of an election and cast a provisional ballot. While not all registered voters will vote in a given election, the percent of eligible voters who are registered establishes a foundation for engagement and serves as one indicator of the health of local democracy, citizen power, and community engagement.

• Data considerations: This measure is derived from registration data. Registration data represent an authoritative list of an event (e.g., voters). Registration data is closer to census data in that it attempts to capture all relevant events to accurately reflect the population. While voter registration can speak to political participation among residents, it is also impacted by whether residents are U.S citizens, have access to registration documents, or are ineligible due to policies like felony disenfranchisement; such determinants are known historically to depress registration among racially minoritized residents.
• How is this measured?: The number of registered voters was taken from the Virginia Department of Elections for 2000-2021. To calculate the percent of registered voters, we divided the number of registered voters by the population of residents aged 18 and over, as estimated by the U.S. Department of Health and Human Services and provided in CDC Wonder.

Income Per Capita

Income Per Capita (IPC) serves as a measure of economic health for a region and is intended to capture the economic development of an area and the standard of living of those residing in the area.

• Data considerations: These data are derived from administrative data, or data collected for the administration of publicly funded programs or services (e.g., state unemployment insurance, state and federal income taxes), and then combined with government surveys. As such, they capture a relatively complete picture of income among the population subject to formal income reporting. While IPC is a common measure of the average income per person, it does not account for the distribution of that income within the population and so can mask significant income inequality. In addition, IPC doesn’t reflect income in the informal economy where transactions are not reported.
• How is this measured?: Area income represents the total sum of the income received by the people in an area. The U.S. Bureau of Economic Analysis measure includes the income that U.S. residents get from paychecks, employer-provided supplements (like insurance), business ownership, rental property, Social Security and other government benefits, interest, and dividends. The Income Per Capita divides this sum by the total population in the area. This calculation distributes the average income across both working populations and populations that do not work or generate income, such as children. The Charlottesville and Albemarle value represents the data from the combined localities of Charlottesville and Albemarle. The inflation-adjusted version uses the Consumer Price Index with 2010 as the base year.

Youth Labor Force Participation and Unemployment

Labor force participation among young people and youth unemployment can shed light on both the health of the economy and the well-being of young people. High unemployment rates for youth may suggest economic struggles or a mismatch between the skills that young people possess and the skills employers are seeking.

• Data considerations: This metric is derived from the American Community Survey (ACS), a continuous survey given to a sample of housing unit addresses each month. Each year the survey releases 5-year estimates, pooling data from all surveyed households throughout a 60-month period. As a survey, rather than a census, the ACS provides estimates of population characteristics and these estimates have a degree of uncertainty, or sampling error, associated with them. Labor force participation and unemployment do not include discouraged workers who have searched for a job in the last year but have given up.
• How is this measured?: The youth labor force participation rate is the number of 15-24 year olds who are employed or are seeking employment as a percentage of the number of residents aged 15-24. The youth unemployment rate is the number of 15-24 year olds who have reported that they do not have a job but are ready to work and have been seeking employment within the last 4 weeks as a percentage of the number of residents aged 15-24 in the labor force.

Children Living below Poverty Threshold

When children grow up in poverty, they are more likely to have inadequate nutrition, limited access to health care services, unstable housing, lower quality of schools, and exposure to environmental toxins, all of which have short- and long-term physical and mental impacts.

• Data considerations: According to the Census, Small Area Income and Poverty Estimates (SAIPE) “are not direct counts from enumerations or administrative records, nor direct estimates from sample surveys. Instead, for counties and states, we model income and poverty estimates by combining survey data with population estimates and administrative records.” As such, these estimates have a degree of uncertainty associated with them.
• How is this measured?: This metric is measured as a percentage of families with incomes below the yearly poverty level out of all families. In 2022, the federal poverty level for a family of four was $27,750.

Students Identified as Economically Disadvantaged

Students are identified as economically disadvantaged if they meet one or more of the following conditions: eligible for free or reduced meals (family income is within 130% or 185% of federal poverty threshold), are eligible for TANF, Medicaid and/or Head Start, or identified as from a migrant family, experiencing homelessness, or in foster care. This measure is an indicator of low-income families. Students in low-income households face additional challenges that can hinder their learning. In addition, education funding is influenced by the presence of economically disadvantaged students via the At-Risk Add-On.

• Data considerations: This metric can be used to provide a picture of the current composition of students from low-income families to the extent economic need has been revealed to and verified by the schools. Historically, eligibility for free or reduced lunch has been one of the most frequent indicators of economic disadvantage; the National School Lunch Program has been a key policy to reduce hunger for children from economically insecure families. The USDA Community Eligibility Provision (CEP) was created in 2010 to allow high-poverty schools an opportunity to apply to offer all students at a school free- or reduced-price-meals. Charlottesville City Schools have been participating in CEP since 2018, and Albemarle County Public Schools began participating in 2022.
• How is this measured?: This measures the count of students identified as economically disadvantaged as a percentage of all students in the school division.

Cost-Burdened Households: Renters and Homeowners

Cost-burdened renters and homeowners are paying more than 30% of their income for housing (rent and utilities or mortgage payments, taxes, insurance, and utilities). Rent burden is an indicator of housing insecurity, as rent-burdened households may struggle to balance paying housing costs with purchasing other necessities. These are also indicators of housing affordability for a region.

• Data considerations: This metric is derived from the American Community Survey (ACS), a continuous survey given to a sample of housing unit addresses each month. Each year the survey releases 5-year estimates, pooling data from all surveyed households throughout a 60-month period. As a survey, rather than a census, the ACS provides estimates of population characteristics and these estimates have a degree of uncertainty, or sampling error, associated with them. In addition, this metric does not reflect housing quality – some households may choose to live in lower-quality housing to reduce costs – or other costs associated with housing, like transportation.
• How are these measured?:
  • The monthly rent paid by a household is divided by the household’s monthly income. Any renting households for which this ratio exceeds 30% are identified as cost-burdened renters. The percentage of cost-burdened renters is the count of these cost-burdened households over the number of all renter-occupied households in an area.
  • The monthly housing costs paid by a household (mortgage, mortgage insurance, real estate taxes, utilities) is divided by the household’s monthly income. Any owner-occupied households for which this ratio exceeds 30% are identified as cost-burdened homeowners. The percentage of cost-burdened homeowners is the count of these cost-burdened households over the number of all owner-occupied households in an area.

People Experiencing Homelessness

The Point-in-Time (PIT) count is conducted each year in January to document the scale and nature of homelessness in our area. The U.S. Department of Housing and Urban Development requires that every Continuum of Care (or CoC, the regional or local planning body that coordinates housing and services funding for homeless families and individuals) conduct a Point-in-Time count at least every other year. In addition to identifying needs and informing policy, the PIT count is a reflection of housing affordability in the region.

• Data considerations: The PIT count is intended to be a complete count of individuals in emergency shelters and who are unsheltered at a given point of time. It cannot capture individuals or families who are without secure housing and staying with family or friends or in short-term hotels.
• How is this measured?: The PIT count is a “count of sheltered and unsheltered homeless persons carried out on one night in the last 10 calendar days of January.” The Blue Ridge Area Coalition for the Homeless (BRACH) is our regional CoC and has conducted the PIT count annually. See HUD for more.

Prenatal Care

Prenatal care is the health care that individuals receive while pregnant. Prenatal care typically includes physical exams, weight checks, urine and/or blood samples, ultrasounds, and discussions about the mother’s and fetus’s health. Prenatal care is important to reduce the risk of pregnancy complications. Late prenatal care is defined as pregnancy-related care beginning in the 3rd trimester (7-9 months). Research has demonstrated that prenatal care dramatically reduces the negative effect of substances during pregnancy, including decreasing the risks of low birth weight and prematurity. Reducing barriers to prenatal care has been a priority of the Blue Ridge Health District’s MAPP2Health Community Assessment and Improvement Plan since 2008.

• Data considerations: These data are derived from health registration data. Registration data represent an authoritative list of births known to the Department of Health. Registration data is closer to census data in that it attempts to capture all relevant events to accurately reflect the population. Error may be introduced if relevant events are not captured.
• How is this measured?: This metric is based on Virginia Department of Health’s Vital Events Statistics program and records the number of mothers who have received adequate prenatal care as a percent of the total number of live births with residence in the area.

Low Birth-Weight Infants

Low birth-weight is an indicator of current infant and maternal health, as well as future health, as low birth-weight babies are at higher risk of dying early, and long-term health and development issues. Low birthweight is defined as less than 2,500 grams (about 5.5 lbs).

• Data considerations: These data are derived from health registration data. Registration data represent an authoritative list of births known to the Virginia Department of Health. Registration data is closer to census data in that it attempts to capture all relevant events to accurately reflect the population. Error may be introduced if relevant events are not captured.
• How is this measured?: This metric is based on Virginia Department of Health’s Vital Events Statistics program and records the number of live births of babies weighing less than 2,500 grams as a percent of the total number of live births with residence in the area.

Infant Deaths

Infant mortality measures the rate at which babies die before their first birthday per 1,000 live births. Infant mortality is an indicator of infant health; the most common causes of infant mortality include birth defects, preterm birth and low birth weight, maternal complications of pregnancy, Sudden Infant Death Syndrome, and injuries.

• Data considerations: These data are derived from health registration data. Registration data represent an authoritative list of births known to the Virginia Department of Health. Registration data is closer to census data in that it attempts to capture all relevant events to accurately reflect the population. Error may be introduced if relevant events are not captured.
• How is this measured?: This metric is based on Virginia Department of Health’s Vital Events Statistics program and records the number of infant deaths as a percent of the total number of live births with residence in the area.

Teen Pregnancies and Births to Teens

According to the VDH, teen pregnancy has unique medical risks – lack of prenatal care, high blood pressure, premature birth, low birth weight, STDs, and postpartum depression. Apart from health concerns, teen pregnancy also has serious social and economic consequences. Teen births are more likely to lead to poor outcomes for both teenage mothers and their children.

• Data considerations: These data are derived from health registration data. Registration data represent an authoritative list of births known to the Department of Health. Registration data is closer to census data in that it attempts to capture all relevant events to accurately reflect the population. Error may be introduced if relevant events are not captured.
• How is this measured?: The teenage pregnancy rate is the sum of live births, legal induced abortions, and natural fetal deaths per 1,000 women aged 15-17 years. The data presented is based on three-year rolling averages.

Sexually Transmitted Infections in Youth

Nationally, the rate of sexually transmitted infections has been on the rise. The CDC estimates that youth ages 15-24 account for almost half of new infections. Adolescents are uniquely at risk for STIs as they are less likely than adults to access and utilize sexual health services and public policies regularly limit young people’s access to sexual health information.

• Data considerations: These data are derived from health registration data. Registration data represent an authoritative list of diagnoses known to the Virginia Department of Health. Registration data is closer to census data in that it attempts to capture all relevant events to accurately reflect the population. Error may be introduced if relevant events are not captured.
• How is this measured?: This measure is the combined incidence of syphilis, gonorrhea, chlamydia, and HIV per 1,000 residents aged 10-19. This incidence rate only counts cases first reported; for HIV, the incidence rate will count a new case in the first year it is diagnosed, but not in the following years, even though a patient still has the condition and is receiving treatment.

Children in Two-Parent Households

Research suggests children living in two-parent households, on average, are more advantaged than single-parent households. Married parent households are typically better off financially and family structure can influence children’s socioemotional development and academic achievement. In addition, lower rates of two-parent households can be indicators of higher rates of divorce/separation or impacted by incarceration trends.

• Data considerations: This metric is derived from the American Community Survey (ACS), a continuous survey given to a sample of housing unit addresses each month. Each year the survey releases 5-year estimates, pooling data from all surveyed households throughout a 60-month period. As a survey, rather than a census, the ACS provides estimates of population characteristics and these estimates have a degree of uncertainty, or sampling error, associated with them. In addition, this measure does not include children living in households with two adults who are not both parents of the child as children living with two parents.
• How is this measured?: The percent of children living with two parents is derived by totaling children ages 0-17 where child/ren are living with both parents and dividing over the total number of children under 18 years in families and subfamilies (multiplied by 100).

Divorce

Divorce rates are one indicator of the health of families. Divorce impacts not only the individuals who are receiving the divorce, but their dependents, income, and assets. Divorce rates are also shaped by marriage rates, which have been declining nationally over time. Additionally, while divorce rates can indicate household instability, they also represent the ability of a spouse to leave a dangerous household. This is important in a larger understanding of community wellbeing as the reasons for divorce are complicated and nuanced.

• Data considerations: These data are derived from administrative data, either data from the Virginia Department of Health (VDH) as part of vital events statistics, or data from the Virginia Judicial System on concluded cases in circuit court. Administrative data can provide a full picture of the population experiencing an event like divorce. However, they do not capture family dissolution outside of those that pursue a legal divorce.
• How is this measured?: The first measure comes from the health department which captures the number of divorce certificates registered with the area’s health department as a percentage of the estimated population of the locality. The second measure comes from circuit court records and captures the number of divorce cases concluded in the circuit court for each locality as a percentage of the estimated population of the locality. Both versions provide the crude divorce rate, a commonly used metric that does not correct for the fact that single people and children are not at risk for divorce.

Assessments and Investigations by Child Protective Services

Reports of potential child neglect or abuse are one indicator of child wellbeing and may signal that more or fewer children are being identified as potentially at risk or that there is greater awareness of the signs of abuse and neglect within the community. Childhood maltreatment, in addition to having an immediate and negative impact on children, has been linked to later physical, psychological, and behavioral consequences.

• Data considerations: Child abuse and neglect referrals are made to Child Protective Services who make a determination of whether the referral meets the threshold and criteria for further action and, if so, whether to pursue a family assessment or an investigation. As such, this measure is not reporting the substantiated occurrence of neglect or abuse, but the valid reporting of potential neglect or abuse. These data, then, capture only cases that have been reported to CPS and screened in by social services. Reports to CPS require someone to observe or evaluate behavior as meeting a threshold of neglect or abuse, and research has demonstrated the deep overlap between the conditions of poverty and of child neglect. The majority of accepted referrals to CPS are made for “physical neglect,” an occurrence open to considerable interpretation.
• How is this measured?: This metric captures the number of referrals to Child Protective Services accepted for assessment or investigation in Virginia, regardless of outcome, over the number of children aged 0-17 in the area and multiplied by 1,000.

Children in Foster Care

Children in foster care are among our most vulnerable children. The rate of family separation is both an indicator of child welfare and of the unmet need or underinvestment in policies and resources to support families in the community. Neglect, often a proxy for the effects of poverty, is one of the most common reasons for a child’s removal from the home nationally, including “failure to provide adequate nutrition, supervision, health care, clothing, or housing.”

• Data considerations: While this data counts all children in foster care at a point in time, a child’s presence in foster care occurs only after multiple decisions made by people in a position of authority. These data, then, reflect a series of actions, evaluations, and decisions, many of which are subject to interpretation. Research has long shown that minoritized populations, especially Black children, are overrepresented in foster care, and legal and social researchers have repeatedly documented the ways child welfare systems are entangled with race.
• How is this measured?: This metric reports the number of children in foster care on October 1 of each year divided by the number of children aged 0-17 in the area and multiplied by 1,000.

School Reports of Discipline (Alcohol and Drug Violations, Physical Violence, and Weapon Possession)

These data capture the recorded student offenses relating to alcohol and drug violations, incidents of physical violence, and possession of weapons in schools. These measures offer insight into student safety and health as well as risk behaviors and involvement with law enforcement. For each metric, it is the rate of incidents per 1,000 students; this is not equivalent to the number of students reported for an offense as an individual student could be reported multiple times.

• Data considerations: These data are derived from school administrative data from the Virginia Department of Education (VDOE). They capture only incidents observed and reported by school authorities. That is, these records do not occur by default but require someone to observe or evaluate an action or behavior and make a judgment about whether the behavior should be referred to the administrative systems. Consequently, these data provide a picture of characteristics that were captured with discretion – some events are surely not observed, and among observed events some are not reported. These data, then, do not necessarily provide a complete representation of relevant events. Further, the requirements for reporting these disciplinary data have changed over time, as have the categories of behaviors. Thus, the records from earlier reports (2006-07 to 2016-17) may not be completely comparable to the records from recent reports (2017-18 to 2020-21).
• How are these measured?: For each measure, the number of relevant incidents from the Discipline, Crime, and Violence (DCV) Annual Report are summed and the total is divided by the number of students in the school division (and multiplied by 1,000). DCV reports for the 2013-14 through 2016-17 school years do not provide school division summaries.
  • Alcohol and drug violation reporting categories for 2017-18 through 2020-21 are “Alcohol violations” and “Drug violations;” for 2006-2007 through 2016-17 categories are “Alcohol”, “Drug violations”, and “Possession/use/sale/distribution of OTC.”
  • Physical violence reporting categories for 2017-18 through 2020-21 are “Assault/Battery”, “Fighting/Conflict”, “Kidnapping”, “Robbery/Person/Force or Threat of Force”, “Sexual Offenses”, “Threats/Verbal/Physical;” for 2006-2007 through 2016-17 categories are “Aggravated sexual battery”, “Battery against staff w/o weapon”, “Battery against student w/o weapon”, “Fighting w/o injury”, “Homicide”, “Kidnapping”, “Malicious wounding”, “Robbery using force”, “Sexual assault”, “Sexual battery”, “Sexual offenses”, and “Threat.”
  • Weapons possession reporting category for 2017-18 through 2020-21 is “Weapons;” for 2006-2007 through 2016-17 categories are “Handgun, rifle/shotgun and other firearms”, “Other weapons and explosive devices”, “Possession of taser/stun gun”, “Possession of razor blades, box cutters”, “Possession of a toy or look alike gun”, and “Possession of fireworks.”

Out-of-School Suspensions

School suspensions are an exclusionary disciplinary tool that temporarily removes students from their schools for a violation of school policies or rules. Being suspended from school is associated with multiple poor outcomes including lower academic achievement, lower quality relationships with teachers, and involvement in the criminal justice system. A 2016 report by the Legal Aid Justice Center noted the majority of suspensions issued statewide in Virginia were for “non-violent, relatively minor misbehavior.”

• Data considerations: These data are derived from school administrative data from the Virginia Department of Education (VDOE). They capture only individuals and incidents observed and reported by school authorities. That is, these records do not occur by default but require someone to observe or evaluate an action or behavior and make a judgment about whether the behavior should result in a suspension. Consequently, these data provide a picture of characteristics that were captured with discretion. In addition, VDOE suppresses counts for suspensions if they are less than 10. Data for long-term suspensions was suppressed in several years for both Albemarle County Public Schools (ACPS) and Charlottesville City Schools (CCS), so these counts slightly underestimate the number of suspensions. This metric presents the number of suspensions per 1,000 students; this is not equivalent to the number of students suspended as an individual student could be suspended multiple times.
• How is this measured?: Out-of-school suspensions include short-term suspensions, long-term suspensions, and modified expulsions to suspensions. The rate of students suspended is the count of students given an out-of-school suspension divided by the total students enrolled in a school division, multiplied by 1,000.

Children in Need of Services or Supervision

This measure tracks the number of judgments of a child in need of supervision, a young person who is truant or has run away from home, and the number of judgments of a child in need of services, a young person whose behavior, conduct, or condition presents or results in a serious threat to himself or another person. A CHINS petition can be filed by parents, police, and school authorities and is adjudicated in Juvenile Court. According to Virginia Code § 16.1-278.4 and § 16.1-278.5, a child who has been found in need of services or supervision may be subject to probation, transfer of custody, or rehabilitative treatment.

• How is this measured?: This metric counts the number of judgments of children in need of supervision and children in need of services issued in a court jurisdiction divided by the number of residents aged 10-17 in the locality (multiplied by 1,000).

Juvenile Delinquency Judgments

This measure tracks the number of judgments of delinquency in the Juvenile and Domestic Relations court. A delinquent judgment may be passed when someone under age 18 commits an act which would be a crime if committed by an adult (including felonies and misdemeanors) and a ruling of delinquency entails escalated involvement with the justice system. According to Virginia Code § 16.1-278.8, juveniles found to be delinquent may be subject to multiple types of sanctions or services: commitment to juvenile justice, probation, substance abuse treatment, fines and restitution, loss of driver’s license, public service project, and others.

• Data considerations: These data do not include “status offenses”, behaviors that are not crimes but are prohibited because of a youth’s status as a minor.
• How is this measured?: This metric counts the number of juvenile delinquency judgments issued in a court jurisdiction divided by the number of residents aged 10-17 in the locality, multiplied by 1,000.

Underage Alcohol Arrests

This measure tracks the rate of arrests for alcohol use in youth under 18 years old. Underage drinking, while common, is associated with multiple risks for young people, including injury, educational struggles, and physical or sexual violence. This measure does not reflect the prevalence of underage drinking, but the intersection of drinking and policing choices and observation. The majority of underage alcohol use does not result in arrest.

• Data considerations: Arrest data capture only instances observed by or reported to police and instances which policing authorities evaluate as being subject to arrest. Multiple selection mechanisms impact the generation of an arrest, including policies and resources as well as the age, race, gender, and class of youth. Additionally, while the legal drinking age in Virginia is 21, these data do not include individuals aged 18-21 as underage arrests.
• How is this measured?: The arrest rate is the sum of arrests among juveniles for driving under the influence, liquor law violations, or drunkenness, divided by the number of residents aged 10-19 (multiplied by 1,000).

Arrests for Violent Crimes

This measure tracks the rate of arrests of youth under 18 for crimes against persons. Arrest data capture only instances observed by or reported to police and instances which policing authorities evaluate as being subject to arrest.

• Data considerations: Multiple selection mechanisms impact the generation of an arrest, including policies and resources as well as the age, race, gender, and class of youth. Additionally, not all crimes generate an arrest and not everyone who is arrested has committed the crime for which they were arrested. Thus, it is important not to equate this metric with the occurrence of crime among youth.
• How is this measured?: The arrest rate is the sum of arrests among juveniles for crimes against persons including murder, negligent manslaughter, kidnapping, sex offenses, aggravated assault, simple assault, and intimidation among juveniles, divided by the number of residents aged 10-19 (multiplied by 1,000).