Inheriting (Im)Possibility
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Transcript of Inheriting (Im)Possibility
Inheriting (Im)Possibility
Marisa BohlmannLisa DeMusisJackie Williams
Inheriting (Im)Possibility is Ezekiel Dixon-Roman’s study on quantitative and
qualitative data and how they affect an individual’s knowledge of an
engagement with the world. His study involves multiple models that
focus on specific relationships between different variables. The first model
presented to us focused on education, wealth, and ethnicity and how they
directly and indirectly affect each other.
The first group of data consists of quantitative elements, such as wealth
and education. Quantitative data represents variables that can be
measured numerically. Alternatively, the qualitative data consists of
parent/child relationship and ethnic background. Qualitative data
is described as information that can be observed but not measured. In the
case of both qualitative and quantitative variables, each can affect
other variables that are within or outside of their own group.
PROJECT INTRODUCTION
The first set of data we received was intensive quantitative charts displaying all
of the variables being studied. The next set of five figures within the first model
was processed into vertical bar graphs by Microsoft Excel. Our challenge was
to fully interpret these graphs that were missing key relationships and pieces of
data that refer back to the original charts.
FIRST TABLES
Inheriting (Im)Possibility | TWO
Aside from the processed graphs, we
were given two flow chart models that
break down the direct and indirect
relationships between all variables of the
study. This includes all assets, maternal/
paternal education, SAT year, parent/
child relationships, environmental factors,
and ACH and SAT performance. The flow
charts along with the previously
mentioned graphs all needed to be
redesigned in a way that would make
them more comprehensible to readers.
FLOW CHARTS
Inheriting (Im)Possibility | THREE
HSAchievement
SAT
Mother/ChildRelationship
Father/ChildRelationship
ENGLISH
FOREIGNLANGUAGE
MATH
SOCIALSCIENCE
LIFE/PHYSICALSCIENCE
VERBAL
MATH
Mother/ChildRelationship
Father/ChildRelationship
Mother/ChildRelationship
M F
Father/ChildRelationship
Maternal GP EDU
Paternal GP EDU
Mother EDU
Father EDU
Log Permanent Outcome
Log Illiquid Asset
Log Liquid Asset
Log Debt
Control Including Race
SAT YearPrivate/Public
School
PhysicalEnvironment
Risk
EnrichingEnvironment
ACH
SAT
ENG
FGN LAN
MATH
SOC SCI
LP SCI
Verbal
Math
FIgure 3: Racial/ethnic differences in wealth holdings
Figure 3 is used to express the differences in median wealth holdings between
ethnicities. These holdings display net worth, total illiquid assests, total liquid
assets, and total debt that are measured in monetary values.
FIGURE 3
Inheriting (Im)Possibility | FOUR
FIgure 4: Racial/ethnic differences in SAT performance
Figure 4 represents the ethnic differences in SAT performances
through unconditioned and full structural models. Unconditioned
focuses exclusively on the child’s education while the full
structural model includes all other factors such as assets.
FIGURE 4
Inheriting (Im)Possibility | FIVE
FIgure 5: SAT wealth gap SAT effect differences
Figure 5 displays how the SAT score differences affect the median wealth
holdings of racial groups. The graph shows that when there is a decrease in
wealth within the groups, the SAT scores decrease as well.
FIGURE 5
Inheriting (Im)Possibility | SIX
FIgure 6: Paternal grandparent education SAT ffects
Figure 6 is the focal point of the model. Since figure 6 shows the direct and
indirect effects of paternal grandparent education on SAT performance, it
embodies the overall concept of the model while the other graphs support
it. The direct effect is the effect using only the grandparent’s level of
education while the total effect accounts for the grandparent’s education
along with all other assets (wealth and race).
FIGURE 5
Inheriting (Im)Possibility | SEVEN
When beginning the redesign process of the graphs, as a group we
decided to edit the information so that it would be easily relatable
throughout the model. Changing graph titles and variable wording
created relationships between variables within the model. Adding
definitions for variables also helps the reader thoroughly understand the
concept of each graph individually and the model as a whole.
Towards the end of the process, after understanding and working with
the model, we rearranged and renumberd the order of the graphs so
that the connections would build on each other. Another design choice
we made was to add negative values to graphs that dealt with integers
below zero and condensing or separating graphs so that each figure
would be displayed with its contextual content. Each change we made to
the model was to make the concept more easily interpretable.
PROJECT INTRODUCTION
On the given flow charts, there were many
overlapping connections that needed to be made
clearer. We began grouping similar variables that
had the same connections. In doing so, line
clutter significantly decreased and made for a less
overwhelming visual. The two flow charts have
been kept separate. The first flow chart simply
shows the variables that make up SAT and ACH
while the second flow chart displays the more
complex connections between developed groups.
Inheriting (Im)Possibility | NINE
FLOW CHART REVISED
Mother
Father
Figure 1: Algorithm of influence
Mother education
Father education
Control including race
Permanent income
Illiquid asset
Liquid asset
Debt
Maternal and paternal
Grandparent education
ACH(Standardized test)
SATACH
(Standardized test)SAT
Accounts for error marginError margin states that the subject being measured can never be 100% accurate.
Structural composition of both ACH and SAT tests. - ACH affects SAT.
Mother/child relationship
Father/child relationship
Public/private school
Physical environment risk
Enriching environment
SAT yearEnglish
Foreign language
Math
Social science
Life/physical science
Verbal
Math
HSAchievement
SAT
Mother/ChildRelationship
Father/ChildRelationship
ENGLISH
FOREIGNLANGUAGE
MATH
SOCIALSCIENCE
LIFE/PHYSICALSCIENCE
VERBAL
MATH
Mother/ChildRelationship
Father/ChildRelationship
Mother/ChildRelationship
M F
Father/ChildRelationship
Maternal GP EDU
Paternal GP EDU
Mother EDU
Father EDU
Log Permanent Outcome
Log Illiquid Asset
Log Liquid Asset
Log Debt
Control Including Race
SAT YearPrivate/Public
School
PhysicalEnvironment
Risk
EnrichingEnvironment
ACH
SAT
ENG
FGN LAN
MATH
SOC SCI
LP SCI
Verbal
Math
Inheriting (Im)Possibility | TEN
Figure 1: Algorithm of influence
Mother
Father
Figure 1: Algorithm of influence
Mother education
Father education
Control including race
Permanent income
Illiquid asset
Liquid asset
Debt
Maternal and paternal
Grandparent education
ACH(Standardized test)
SATACH
(Standardized test)SAT
Accounts for error marginError margin states that the subject being measured can never be 100% accurate.
Structural composition of both ACH and SAT tests. - ACH affects SAT.
Mother/child relationship
Father/child relationship
Public/private school
Physical environment risk
Enriching environment
SAT yearEnglish
Foreign language
Math
Social science
Life/physical science
Verbal
Math
Through the design process, we found that Figure 2 would be most successful if the wealth holdings
could be represented with positive and negative values. Our solution was to create a vertical graph
that contained bars rising above and below the baseline of zero. Total liquid assets, plus total illiquid
assets, minus debt results in net worth. In organizing the variables this way the reader can
understand the connections between wealth assets. Grouping ethnicities with their own wealth
numbers, makes the differences in wealth more obvious.
FIGURE 2 REVISED
Inheriting (Im)Possibility | ELEVEN
Inheriting (Im)Possibility | TWELVE
Figure 2: Racial differences in wealth holdingsFigure 2: Racial differences in wealth holdings
Hispanic Black Sample median White
Value in dollars(1,000’s)
Total illiquid assests Total liquid assets Net worthTotal debt+ =-
0
20
40
60
80
100
120
140
160
-80
-60
-40
-20
Figure 3 portrays the effect of wealth on SAT scores amongst the different racial groups. When
we reexamined the data, we found that the numbers were too close together to emphasize the
resulting difference in a bar graph. We decided that the best way to proceed would be to translate
the data into percentages. By using percentages and reorganizing the data, we could present the
differences in numbers with greater effect.
FIGURE 3 REVISED
Inheriting (Im)Possibility | THIRTEEN
Inheriting (Im)Possibility | FOURTEEN
Figure 3: Grandparent wealth holdings effect differences on SAT scores
$750,000Whitemedian
Samplemedian
Hispanic median
Black median
Figure 3 : Grandparent wealth holdings effect differences on SAT scores
Wealth medians(Total illiquid assets)
SAT scores
0 Assets
1000
1025
1050
+84 +85+92 +96
+108
950
929
975
($154,500)
($0)
($102,500)($37,500) ($43,475)
Bar numerals show increases in scores compared to the baseline of 0 assets.
The SAT scores for Figure 4 proved to be difficult to design. Being so close together, many graphs
and charts did not emphasize the difference in scores between Black and Hispanic ethnicities within
the unconditioned and full structural models. After working with a point and line graph for a period
of time, we came to the conclusion that separating the unconditioned and full structural models
would be the best option. The bars, from left to right, measure a quantity. Using true SAT scores
that start at 400 (the lowest SAT score possible), each bar extends to the achieved SAT score on a
scale that caps at 1600.
FIGURE 4 REVISED
Inheriting (Im)Possibility | FIFTEEN
Inheriting (Im)Possibility | SIXTEEN
Figure 4: SAT performance differences between racial groups
400 1600
Unconditioned Model
Black
Hispanic
White
851
879
1062
400 1600
Full Structural Model
Black
Hispanic
White
935
941
1021
Figure 4: SAT performance differences between racial groups
SAT scores
SAT scores
- Unconditioned includes just SAT year and race variables.- Full structural includes all of the variables and their connections in figure 1.
- Unconditioned includes just SAT year and race variables.- Full structrual inclueds all of the variables and their connections in figure 1.
In Figure 5, direct and total effect needed to be displayed in a way that showed the positive
correlation between paternal grandparent education and grandchildren’s SAT scores. Instead of
using a bar graph that is static and evenly spaced, we chose to design a line graph that showed the
rise in education and SAT scores as a steady incline. We also chose to represent the scores in true
SAT score form. Doing so helps the reader to fully understand the context of the numbers. Data for
Figure 5 is still being tested, and therefore may redetermine the state of the final graph.
FIGURE 5 REVISED
Inheriting (Im)Possibility | SEVENTEEN
Inheriting (Im)Possibility | EIGHTEEN
Figure 5: Paternal grandparent education effects on SAT performanceFigure 5: Paternal grandparent education effects on SAT performance
4th grade
Direct effect
SAT scores
Total effect
8th grade HS diploma orequivalent
Bachelor’sdegree
Graduate orprofessionaldegree
1550
0
1300
1350
1400
1450
1500
1600
Direct effect includes just grandparents’ influence on SAT scores.Total effect includes grandparents’ connection to all other variables in figure 1.
- -
In order to complete designing model one, we
will need to rework and fine tune some aspects of
each figure. We would also like to consider
creating color versions, to give the publisher
variety. As we finish up with the current model, we
will begin to discuss continuing onto other
models after the course ends. We will be able to
take the skills and techniques we have learned
from designing the first model and apply them to
the upcoming models in a concise, relative way.
CONCLUSION