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\begin{document}
\begin{CJK}{UTF8}{gbsn}

\title{NYC Foster Care Data Challenge}



\author[1]{Samantha Pepe}%
\author[2]{Mae Jemison}%
\author[1]{Jie Gao}%
\author[1]{chen chen}%
\affil[1]{Affiliation not available}%
\affil[2]{Authorea}%


\vspace{-1em}



  
  \date{April 25, 2026}


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\textbf{Team: Data Enthusiasts}

\textbf{Design Challenge 1}

\textbf{Samantha Pepe \textbar{} Chen Chen \textbar{} Jie Gao}

\textbf{1. Introduction}

Foster care in New York City has been constantly providing shelter for
children who are neglected or in need. Matching potential foster
families with the adopted children is never an easy task which calls for
resources, time and most importantly, analytical research. Our
statistical report will comment on the current foster care situation in
terms of demographics, child history, and types of foster placement.
Using these insights we will attempt to provide recommendations on how
to make New York City's foster care more efficient.

\textbf{2. Data}

For our analysis , we will use two Adoption and Foster Care Analysis and
Reporting System (AFCARS) datasets for adoption and foster care .The
AFCARS adoption dataset contains 1,933 New York State adopted children's
statistics, and the foster care data set includes 11,571 subjects. In an
attempt to make the AFCARS dataset more New York City specific, these
subjects are from filtering those that did not place out of New York
state, and live in an area with a population over one million (urban
continuum code=1). In addition, we will use two NYTD (National Youth in
Transition) data for subjects in New York state. NYTD outcome data
consists of variables concerned with the well being of adults 18+ who
were in the foster care system (N=2446) .NYTD services data consists of
information that reflects whether or not those who were in foster care
utilized resources (financial assistance, mentoring, etc)

\textbf{3. Questions}

\textbf{What is the profile of existing foster families in New York?}

To answer this question, we first looked at where the foster children in
New York City are coming from. Figures 1 and 2 show a visualization of
where the children are from in the city and the poverty rate of each
area. It is evident from these visuals that In fact, the correlation
between foster children and poverty rate in each given district was .63
for 2013 and .61 for 2014. The area that has the highest correlation
between these two variables is central Harlem. In this area, 62\%
residents are black and 23\% residents are Hispanic. 29\% of residents
of Central Harlem live below the Federal Poverty Level and Central
Harlem is the second-poorest neighborhood in Manhattan.~

\par\null\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/fostercareplacements2014/fostercareplacements2014}
\caption{{Foster Child's Place of Origin
{\label{144322}}%
}}
\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/percentpoverty3/percentpoverty3}
\caption{{2015 Poverty Rate By Location~
{\label{740791}}{\label{740791}}%
}}
\end{center}
\end{figure}

Figures 3 and 4 give the demographic breakdown of foster families, using
the data from AFCARS Foster. Both caretakers and foster children are
dominantly African American, followed by Caucasian and Hispanic. As
shown in figure 5, most foster family are composed of a single female
caretaker, followed by unmarried caretakers, married, and single males.
Single females are disproportionately African American, making up 57
percent of the single female foster caretaker population.

\par\null\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/childreninfoster/childreninfoster}
\caption{{Foster Care Children by Race~
{\label{342008}}%
}}
\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/caretakers/caretakers}
\caption{{Foster Caretaker by Race~
{\label{284862}}%
}}
\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/famstructure/famstructure}
\caption{{Foster Family Structure~
{\label{946475}}%
}}
\end{center}
\end{figure}



\textbf{What makes a family or person an ''optimal'' candidate?}

Despite more African American children being in foster care, a
disproportionate amount of Caucasian children are adopted. According to
the AFCARS data, African American children make up 56\% of the foster
care population but 42\% of the adopted population, while Caucasian
children make up 18\% of the foster population but 33\% of the adopted
population (A .75 adoption:foster care ratio versus a 1.83
adoption:foster care ratio). However, the correlation between African
American foster children and Caucasian foster children suggest that they
are fundamentally different in behavior, family structure, etc ( -.68).
While caucasian foster families and adoptive parents are often married,
african american foster families and adoptive parents are often single
females. Defining the optimal candidate as someone who will eventually
adopt the child, perhaps providing single adoptive mothers a greater
monetary benefit will close this adoption gap. Compared to married
families single mothers make significantly less money in the United
States and may not be able to afford to adopt a child.

Another preferable characteristic of a foster family is that they are
not a group home or institution, but rather they are fostering a few
children at a time. A logistic regression {[}3{]} predicting goal of
adoption signifies that those in a group home, institution, or even a
family member's home are less likely to establish their goal as
adoption.

\textbf{How can you build segments to target where more families can be
found?}

One of our strategies to find more families actually calls for
desegmentation. Through a chi square test {[}4{]} we found that in fact
there is a proven bias in terms of race. Specifically, African americans
are biased towards african american children and away from caucasian and
hispanic children. Hispanics and Caucasians are biased towards hispanic
and caucasian children and away from African American children. Perhaps
more advertisements of multicultural families and embracing diversity
could change these statistics. Ultimately, the segment we are trying to
reach is those that will adopt children of a different race.

Another segment to target could be single males{[}3{]} . Although they
are the least represented in foster family structures, the logistic
regression predicting a goal of adoption shows single males to be a
positively significant predictor.

\textbf{How Can We Encourage More Families to Sign Up?}

As stated previously, a disproportionate amount of single mothers are
fostering children. Perhaps even more would do so if they were given
child assistance. The city could provide a set amount of hours of
babysitting services to foster parents which would especially aid these
foster parents who do not have a partner to help them. This subgroup
might perceive foster care as more manageable.

\textbf{One more note} A staggering statistic we found was a correlation
of .75 between a previously in foster care youth having a child and
homelessness. Perhaps providing free/reduced birth control to the foster
care population could prevent future homelessness,poverty, and a
recurring cycle of foster care.

\textbf{Appendix:}

\textbf{{[}1{]}}

\textbf{Variables with Significant Correlations (Correlation
\textgreater{}.5 or \textless{}-.5)}\selectlanguage{english}
\begin{longtable}[]{@{}lll@{}}
\toprule
Variables & Correlation & Source\tabularnewline
\midrule
\endhead
Adoptive mother asian \& adopted child asian & .58 & AFCARS
Adoption\tabularnewline
Adoptive mother asian \& adoptive father asian & .82 & AFCARS
Adoption\tabularnewline
Adoptive mother hispanic \& adoptive father hispanic & .57 & AFCARS
Adoption\tabularnewline
Adopted child african American \& Adoptive Family Married & -.89 &
AFCARS Adoption\tabularnewline
Adopted African American Child \& Adopted Caucasian child & -.70 &
AFCARS Adoption\tabularnewline
Adoptive mother native american \& adoptive father native american & .58
& AFCARS Adoption\tabularnewline
Goal adoption and in preadoptive home & .60 & AFCARS
Foster\tabularnewline
African American foster child \& Caucasian foster child & -.68 & AFCARS
Foster\tabularnewline
African American foster child using services and Caucasian foster child
using services & -.73 & NYTD Service\tabularnewline
Caucasian foster child using services and hispanic foster child using
services & .50 & NYTD Service\tabularnewline
Age receiving services and in foster care & -.53 & NYTD
Service\tabularnewline
Financial public assistance and public housing assistance & .73 & NYTD
Outcome\tabularnewline
Financial public assistance and public food assistance & .53 & NYTD
Outcome\tabularnewline
Foster youth having child and homelessness & .75 & NYTD
Outcome\tabularnewline
\bottomrule
\end{longtable}

\par\null\par\null\par\null\par\null

\textbf{Figure 1 Correlation Plots:}\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/adopthome1/adopthome1}
\caption{{Source: AFCARS Adoption~
{\label{986701}}%
}}
\end{center}
\end{figure}

\textbf{Source: AFCARS Foster Care:}

\textbf{}\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/foster/foster}
\caption{{AFCARS Foster~
{\label{606404}}%
}}
\end{center}
\end{figure}

\textbf{}\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/service/service}
\caption{{NYTD Services
{\label{417488}}%
}}
\end{center}
\end{figure}

\par\null

\textbf{}\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/outcomes/outcomes}
\caption{{NYTD Outcomes
{\label{180264}}%
}}
\end{center}
\end{figure}



\textbf{{[}2{]} Correlations between foster placements by district and
boroughs}

\par\null\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/tecor/tecor}
\caption{{NYC Opendata Placements by District
{\label{880821}}%
}}
\end{center}
\end{figure}



\textbf{{[}3{]}Logistic Regression}

\par\null

\textbf{}\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/predictgoaladopt/predictgoaladopt}
\caption{{Source: AFCARS Foster~
{\label{223395}}%
}}
\end{center}
\end{figure}



\textbf{{[}4{]}}

\textbf{}\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/chidifference/chidifference}
\caption{{Chi Test Race Child vs Race Guardian
{\label{616008}}%
}}
\end{center}
\end{figure}

Chi Square Differences (counts are included in csv file)

\par\null\par\null

Github URL: https://github.com/smpepe/fostercare

Sources:

\begin{enumerate}
\tightlist
\item
  Adoption and Foster Care Analysis and Reporting System (AFCARS),
  Adoption File
\item
  Adoption and Foster Care Analysis and Reporting System (AFCARS),
  Foster File
\item
  National Youth in Transition Database (NYTD) - Outcomes File, FFY 2015
  (Cohort 1, Wave 3)
\item
  National Youth in Transition Database (NYTD)- Services File, FFY 2015
\item
  NYC Community Health Profiles
  (https://www1.nyc.gov/site/doh/data/data-publications/profiles.page)
\item
  NYC Social Service Placements by Communty District
  (https://data.cityofnewyork.us/Social-Services/Placements-by-Community-District-CD-/xg3x-h3g7)
\end{enumerate}

\par\null

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