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August 12, 2022
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This bulletin describes the official juvenile court
referral histories of more than 160,000 youth born in 2000
from 903 selected United States counties. Using data from
the National Juvenile Court Data Archive, this bulletin
focuses on the demographic and case processing
characteristics of youth referred to juvenile court and
the proportion of the cohort that was referred to juvenile
court more than once, as well as histories defined as
serious, violent, and chronic. More than 60% of youth in
the cohort did not return to juvenile court after their
first referral. A small percentage of youth (7%) were
initially referred to juvenile court for a violent crime.
Additionally, the data indicates that the likelihood of
referrals varied by demographics. Males are still more
likely to return to juvenile court than their female
peers. Black and American Indian youth were most likely to
be referred more than once.
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Source: U.S. Department of Justice, Office of Justice
Programs
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Intimate partner abuse solution (IPAS) programs were first
developed in the 1970s and have historically been referred
to as batterer intervention programs. Although these
programs are now known by different labels and apply
different approaches and philosophies, collectively they
are designed to prevent intimate partner violence by
holding perpetrators accountable for their behavior and
prioritizing safety and justice for victims. Despite
widespread adoption and use of IPAS programs by court
systems and communities around the United States, there
remains inconsistent and limited information on their
effectiveness. For this report, the authors convened a
panel of experts to better understand the needs of these
programs. The panel identified 33 high-priority needs,
which cover four major areas: content covered in current
IPAS programs; program implementation; connections between
IPAS programs and criminal justice and community entities;
and challenges in conducting rigorous research on IPAS
programs. The report found that state regulations around
IPAS programs are often very prescriptive, which prevents
states from altering or shifting their approaches.
However, the report also found there is considerable
variation in the logistics of how IPAS programs are run
and limited research on how logistical factors affect
participation. The report makes recommendations including
developing evidence-informed federal guidance on shifting
state standards around IPAS programs and conducting
research on the impacts of program logistics on
participation, including best practices in incorporating
virtual options into in-person programs.
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Source: RAND Corporation
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The Justice Reinvestment Initiative (JRI) is a data-driven
approach to managing criminal justice populations and
investing savings in recidivism reduction strategies and
improved public safety funded by the U.S. Bureau of
Justice Assistance and Pew Charitable Trusts. Through JRI,
states have made a range of changes to their justice
systems, and many states have decreased their prison
populations or kept them below projected levels. This
report discusses four states’ programs and approaches that
are now critical components of their justice systems and
represent the diverse challenges and solutions of states
that have participated in JRI. The programs and approaches
discussed in the report include: Arkansas’s crisis
stabilization units and crisis intervention training;
Louisiana’s gender-responsive approach to women’s
incarceration and supervision; Oregon’s Improving People's
Access to Community-Based Treatment, Supports, and
Services (IMPACTS) program; and Pennsylvania’s
performance-based contracting approach to community
corrections. The report outlines each program or
approach’s implementation process, changes, and/or
challenges since its inception, and perceived or
documented outcomes. Additionally, the report presents key
takeaways and from each program or approach.
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Source: Urban Institute
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The Texas Education Agency offers grants for districts to
implement school turnaround strategies at low-performing
schools. Districts that receive these grants can implement
a school turnaround strategy (referred to as a
district-managed restart strategy) that includes replacing
principals and teachers at schools that the district
identifies as struggling and needing additional support.
From 2015-16 to 2018-19, 29 schools across four urban and
suburban districts in Texas implemented a district-managed
restart strategy in three cohorts: one district began in
2015-16, another in 2017-18, and two in 2018-19. This
study used longitudinal administrative data and interviews
with district and school leaders to examine implementation
of the restart strategy and its effects on teacher and
principal mobility, student achievement, and student
attendance. State leaders can use the results of this
study to make decisions about continuing to offer grants
for districts to implement the district-managed restart
strategy in their low-performing schools. Key findings
include that 1) nearly 80% of the teachers at schools in
the year before implementation of the restart strategy
left before the beginning of the restart school year; 2)
educators who arrived at restart schools were more likely
to have more than three years of experience and to have an
advanced degree than those who left or stayed; 3) student
achievement and attendance improved after schools
implemented the restart strategy; 4) nearly all restart
schools met accountability standards within the first
three years of implementation; and 5) interviews with
district and school leaders suggested that recruiting
high-performing teachers to relocate to restart schools
was time consuming and that the grant-funded salary
stipend might not have been a large enough incentive.
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Source: U.S. Department of Education, Institute of
Education Sciences
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This study, commissioned by the United Kingdom’s
Department for Education, finds that skills related to
knowledge and relevant technologies are required in the
next 5–10 years. Digital literacy is already an essential
requirement, with degrees of digital skills required in
different sectors and occupations. However, across roles,
skills around understanding of data will only increase in
importance as responsibilities for data handling and
security are shared across organizations. Some specific
technical skills are needed in health and trades such as
those related to the ability to adapt clinical skills to
developments in health and care, knowledge of the
technical basis of work and understanding of relevant
standards and legislation. Expected changes in the
occupations and emerging skills point to: (i) skills needs
in using specific new hardware; (ii) data science skills;
(iii) the need to apply skills to future-related goals.
Participants suggested that the promotion of multiple
routes into occupations, along with clear definitions of
skills and qualifications, should be improved. People and
communication skills are and will continue to be needed,
including to complement the use of digital skills and
communicate about these with colleagues and the public.
Teamwork skills are and will be key in addressing complex
needs in coordinated way. Skills around planning and
communicating long-term strategy, exploiting
opportunities, and managing risks were seen as especially
important for managers and health professionals.
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Source: RAND Corporation
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A growing number of institutions and state systems of
higher education are embracing co-requisite developmental
education (DE) models whereby students take developmental
(or remedial) courses in the same semester as the
associated introductory college-level English or math
course. This model abandons the traditional notion that
students must complete all DE courses before taking
college-level courses and a growing number of studies have
found that co-requisite models have been associated with
large gains of 10 percentage points or more in the
likelihood of successfully completing gateway courses in
math or English in the first year relative to traditional
DE models. Texas permits individual institutions to decide
how to offer co-requisite course option in terms of both
structure and intensity. In terms of structure,
institutions can decide to offer the course concurrently
or paired with the associated introductory college-level
course, sequentially where students complete the DE
portion before the college-level portion (but both within
the same semester), or via a non-course competency based
option that can take on the form of lab hours, tutoring,
or other formats. In terms of intensity, institutions can
also decide how many credits the courses bear, ranging
from 0 to more than 4 credit hours. In this report, the
authors present findings from a year-long study that
investigated (1) how student success in integrated reading
and writing/ English and math is related to the structure
and intensity of co-requisite course options and (2) the
decisions institutional leaders and instructors made when
deciding which options to offer. The main findings
include: 1) students enrolled in sequential courses tended
to be more likely to pass the integrated reading and
writing course (77.71%) compared to students in concurrent
(69.22%) and non-course competency based option courses
(57.67%); 2) the likelihood of passing the integrated
reading and writing course was similar for all students
regardless of the number of credits of the integrated
reading and writing course; 3) the likelihood of passing
DE math was the greatest for students in sequential
co-requisites, with a predicted probability of passing DE
math of 82.10% for sequential co-requisites relative to
63.29% for non-course competency based option courses and
62.03% for concurrent co-requisites; and 4) there are few
differences in the likelihood of passing a gateway math
course by co-requisite structure or intensity.
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Source: Florida State University, Center for Postsecondary
Success
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Wealth is the value of assets owned minus the liabilities
(debts) owed. As described in a previous report on
household wealth in 2017, this new U.S. Census Bureau
report and detailed tables on household wealth in 2019
show similarly wide variations across demographic and
socioeconomic groups, but also detail generational wealth
differences for the first time. For example, it shows that
baby boomers are nearly nine times wealthier than
millennials. Just two assets — home equity and retirement
accounts — accounted for 65.2% of households’ wealth in
2019. Households that owned their home had a median wealth
of $305,000, substantially larger than those that rented
($4,084). Not surprisingly, Generation Z, the youngest
generation with adult members (born 1997 to 2013), had
less wealth than the oldest and wealthiest Silent
Generation (born 1928 to 1945): median wealth of $3,080
compared to $253,200. Millennials, who were between 23 and
38 years old by the end of 2019, also had less wealth
compared to other older generations. Millennials had a
median wealth of only $27,420, while Generation X (born
1965 to 1980) had $121,400 and baby boomers (born 1946 to
1964) had a median wealth of $240,900. When excluding home
equity, Generation X and baby boomers had a median wealth
of $48,070 and $90,060, respectively.
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Source: U.S. Department of Commerce, Census Bureau
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Artificial intelligence and machine learning analyses are
driving critical decisions impacting our lives and the
economic structure of our society. These complex
analytical techniques—powered by sophisticated math,
computational power, and often vast amounts of data—are
deployed in a variety of critical applications, from
making healthcare decisions to evaluating job applications
to informing parole and probation decisions to determining
eligibility and pricing for insurance and other financial
services. Artificial intelligence and machine learning
models might replicate, amplify, or introduce new sources
of bias. Models that rely on latent features identified by
the learning algorithm rather than intentionally
programmed into the models by developers could reverse
engineer applicants’ race or gender from correlations in
the input data or create complex variables that have
disproportionately negative effects for particular
demographic groups. The complexity of machine learning
models makes them more challenging to explain to audiences
for purposes of informing their downstream activities.
This dynamic affects data scientists, compliance
personnel, and regulators who need to perform specific
oversight functions, as well as individual credit
applicants who are seeking to improve their chances of
future credit approvals. Especially for non-technical
audiences, explaining which features are influential to
particular lending decisions can be difficult when the
models rely on data relationships that are inherently
complex, non-intuitive, large in number, or dependent on
other variables or relationships. The report findings lead
for a call for stakeholders to engage in a dialogue
centered around three core issues: the consumer
experience, fairness and inclusion, and model risk
management. These conversations should help to advance how
public policy and market practice leverage the accuracy
and fairness benefits of machine learning techniques while
deploying the technology in ways that are sufficiently
transparent. Research and stakeholder dialogue will help
to inform a roadmap for evolving market practices and
public policy to produce an era of more inclusive and fair
credit underwriting.
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Source: Brookings Institute
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Building off of past roundtable conversations around the
passage of the federal bipartisan infrastructure law in
2021 and its unprecedented levels of funding for wildfire
resilience work, this workshop brought together state,
Tribal, federal, non-government organizations, and other
experts to create a shared understanding of the scale,
distribution, and impacts of post-fire reforestation
needs; explore what is being done to address them; and
develop recommendations to address gaps and barriers. This
summary captures key points from presentations provided
during the workshop, along with key topics of discussion.
Increasing the resilience of forests to wildfire involves
mitigating risk through forest management pre-fire, but
also reforestation and restoration work in forests and
watersheds after fire occurs. This post-fire management is
essential to make sure the landscape can regenerate, be
healthier, and better withstand the next fires.
Reforestation encompasses a suite of activities, from
selection of genetically appropriate species and seeds,
stock-type, site preparation, out-planting techniques and
windows, to planning for post-planting monitoring.
Reforestation ensures that forests can continue to provide
clean water and carbon storage, among a host of other
benefits. Given the current rates of reforestation, it
would take decades to address the existing need, without
taking into account future disturbances; a shortfall which
has sparked new laws and funding for the U.S. Forest
Service. The REPLANT Act, which was part of the 2021
Bipartisan Infrastructure Law, is the most significant
piece of legislation since 1980 for reforestation on
national forests. Among its key provisions, the Act
directs the agency to develop a new strategy and process
to prioritize disturbance-caused reforestation needs, sets
a 10-year target to address the reforestation backlog on
U.S. Forest Service lands, and adds additional reporting
requirements.
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Source: Aspen Institute
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This report presents complete period life tables for the
United States by Hispanic origin, race, and sex, based on
age-specific death rates in 2020. In 2020, the overall
expectation of life at birth was 77.0 years, decreasing
1.8 years from 78.8 in 2019. From 2019 to 2020, life
expectancy at birth decreased by 2.1 years for males (76.3
to 74.2) and by 1.5 years for females (81.4 to 79.9). In
2020, life expectancy decreased from 2019 by 4.7 years for
the non-Hispanic American Indian or Alaska Native
population (71.8 to 67.1) and by 4.0 years for the
Hispanic population (81.9 to 77.9), 3.3 years for the
non-Hispanic Black population (74.8 to 71.5), 2.0 years
for the non-Hispanic Asian population (85.6 to 83.6), and
1.4 years for the non-Hispanic White population (78.8 to
77.4). At 77.0 years, U.S. life expectancy at birth for
2020 was the lowest it has been since 2002. Similarly,
male life expectancy (74.2) and female life expectancy
(79.9) declined to levels not seen since 2000 and 2003,
respectively. From 2019 to 2020, the decline in life
expectancy at birth based on the final 2020 life tables
was 0.3 year greater than that based on provisional 2020
life tables for the total, male, and female populations.
The differences are mostly due to differences in mortality
estimates for ages 85 and over.
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Source: U.S. Department of Health and Human Services,
Centers for Disease Control and Prevention
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This report presents 2020 fetal mortality data by maternal
race and Hispanic origin, age, tobacco use during
pregnancy, and state of residence, as well as by
plurality, sex, gestational age, birthweight, and selected
causes of death. Trends in fetal mortality are also
examined. A total of 20,854 fetal deaths at 20 weeks of
gestation or more were reported in the United States in
2020. The 2020 U.S. fetal mortality rate was 5.74 fetal
deaths at 20 weeks of gestation or more per 1,000 live
births and fetal deaths, which was not significantly
different from the rate of 5.70 in 2019. The fetal
mortality rate in 2020 for deaths occurring at 20–27 weeks
of gestation was 2.97, essentially unchanged from 2019
(2.98). For deaths occurring at 28 weeks of gestation or
more, the rate in 2020 (2.78) was not significantly
different from 2019 (2.73). In 2020, the fetal mortality
rate was highest for non-Hispanic Native Hawaiian or Other
Pacific Islander (10.59) and non-Hispanic Black (10.34)
women and lowest for non-Hispanic Asian women (3.93).
Fetal mortality rates were highest for females under 15
and aged 45 and over, for women who smoked during
pregnancy, and for women with multiple gestation
pregnancies. Five selected causes accounted for 89.6% of
fetal deaths in the 43-state and District of Columbia
reporting area. By order of frequency, these were: 1)
Fetal death of unspecified cause; 2) Fetus affected by
complications of placenta, cord and membranes; 3) Fetus
affected by maternal complications of pregnancy; 4) Fetus
affected by maternal conditions that may be unrelated to
present pregnancy; and 5) Congenital malformations,
deformations and chromosomal abnormalities.
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Source: U.S. Department of Health and Human Services,
Centers for Disease Control and Prevention
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On August 4, 2022, the U.S. Department of Health and Human
Services (HHS) Secretary declared a Public Health
Emergency for the monkeypox outbreak. Countries in Africa
have reported monkeypox since the first human case of
monkeypox was identified in 1970 (endemic spread). There
have been limited outbreaks in countries outside of
Africa. Starting in May 2022, clusters of monkeypox cases
were reported in Europe and the United States. Since then,
case counts have increased in non-endemic countries—
representing the largest outbreak in non-endemic countries
in recent history. According to the Centers for Disease
Control and Prevention (CDC), as of August 4, 2022, over
26,800 cases of monkeypox have been confirmed globally,
with over 26,500 cases in countries that have not
historically reported endemic spread of the virus; over
7,000 cases have been confirmed in the United States. On
June 28, 2022, CDC activated its Emergency Operations
Center for monkeypox response. On August 2, 2022, the
White House appointed a Federal Emergency Management
Agency (FEMA) official as the lead coordinator for the
monkeypox response and assigned a CDC official as his
deputy. Other HHS agencies, such as the Administration for
Strategic Preparedness and Response (ASPR; formerly Office
of the Assistant Secretary of Response) and the Food and
Drug Administration (FDA) are also actively engaged in
response efforts. The White House and HHS agencies have
initiated response activities, including supporting
education and awareness and defining federal research
priorities. Some key response activities include (1)
testing; (2) tracking, surveillance, and contract tracing;
and (3) medical countermeasures (including vaccines and
therapeutics).
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Source: Congressional Research Service
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Government Program Summaries (GPS) is a free resource for legislators and the public
that provides descriptive information on over 200 state government programs. To provide
fiscal data, GPS links to Transparency Florida, the Legislature's website that includes
continually updated information on the state's operating budget and daily expenditures
by state agencies.
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A publication of the Florida Legislature's Office of Program Policy Analysis & Government Accountability
PolicyNotes, published every Friday, features reports, articles, and websites with timely information of interest to policymakers and researchers. Any opinions, findings, conclusions, or recommendations
expressed by third parties as reported in this publication are those of the author(s) and do not necessarily reflect OPPAGA's views.
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PolicyNotes provided that this section is preserved on all copies.
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