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Metropolitan USA: Evidence from the 2010 Census
No full textPopulation, Growth, Suburbs, MetropolitanI will review the major changes in the distribution of the metropolitan population of the United States (US), as revealed by the 2010 data recently released by the US Census. These data allow us to track recent changes and provide the basis for a discussion of longer-term trends identified in previous studies of US cities (Short 2006, 2007) and the city suburban nexus (Hanlon et al. 2010). In brief summary, the paper will show the continuing metropolitanization and suburbanization of the US population. A more nuanced picture will reveal evidence of stress in suburban areas and population resurgence in selected central city areas. Overall, the story is one of a profound revalorization and a major respatialization of the US metropolis.Hindawi Publishing Corporation
International Journal of Population Research
Volume 2012, Article ID 207532, 6 pages
doi:10.1155/2012/207532
Review Article
Metropolitan USA: Evidence from the 2010 Census
John Rennie Short
Department of Public Policy, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA
Correspondence should be addressed to John Rennie Short, [email protected]
Received 27 November 2011; Accepted 14 March 2012
Academic Editor: Shirlena Huang
Copyright © 2012 John Rennie Short. This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
I will review the major changes in the distribution of the metropolitan population of the United States (US), as revealed by the
2010 data recently released by the US Census. These data allow us to track recent changes and provide the basis for a discussion of
longer-term trends identified in previous studies of US cities (Short 2006, 2007) and the city suburban nexus (Hanlon et al. 2010).
In brief summary, the paper will show the continuing metropolitanization and suburbanization of the US population. A more
nuanced picture will reveal evidence of stress in suburban areas and population resurgence in selected central city areas. Overall,
the story is one of a profound revalorization and a major respatialization of the US metropolis.
1. The Broad Picture
The mean center of the US mainland population is plotted
for each Census decade since 1790. The point marks the
central fulcrum of the national population. In 1790 the
mean center was located in Maryland and over the years has
steadily moved westward in line with the westward shift of
population. Between 1970 and 1980, the mean center crossed
the Mississippi River, and by 2000 it was located in Phelps
County Missouri. By 2010, it shifted further westwards and
southward to Texas County in Missouri. The slow, steady
shift of the mean center marks the redistribution of the
US population to the expanding metro areas of the South
and West. Its slow progress, however, reminds us of the
continuing population weight of the Northeast.
The mean population center now passes through the
interior of the country, the so-called heartland. Yet it is a
heart with an anemic demographic beat. The population of
six counties in this region—Fayette, Marion, Randolph, and
Shelby in Illinois and Montgomery and Dent in Missouri—
was 144,880 in 1950, rising to only 145,309 in 2010. In
much of the rural interior of the US, the story is one of
continuing relative population decline as the people move
to the city regions. The county that hosted the mean center
of population in 2010—Texas County, Missouri—saw only
slight population increase from 18,992 in 1950 to 26,008 in
2010. The percentage of persons in the county living below
the poverty rate was 24.4 percent in 2010—almost double the
national average—and the median household income was
only three-fifths of the national average. The rural heartland
is losing population and experiencing economic stress.
2. ContinuingMetropolitanization
The drift of population to large cities continues. The US
census employs the term metropolitan statistical area (MSA)
to refer to urban areas with a core area of at least 50,000 and
economic links to surrounding counties. Using this statistical,
rather than political division of municipal boundaries,
it is possible to measure the metropolitanization of the US
population. In 1950 the metropolitan population was just
over a half at 56.1 percent of the total US population. By 2010
the figure was 83.6. The US population is increasingly and
overwhelmingly concentrated in metropolitan areas. More
than 90 percent of the country’s entire population growth in
the last decade occurred within MSAs.
A further 10 percent of the US population lives in
micropolitan statistical areas, which contain an urban core of
at least 10,000 and, in total, have less than 50,000 population.
Only 6.3 percent (versus 6.8 percent in 2000) live outside
these two types of urban areas. The US continues to become
a more urban and metropolitan society.
2 International Journal of Population Research
When we break down the metropolitan areas by size,
there are differential growth rates. Table 1 shows the population
for different sized MSAs from 1980 to 2010. The
greatest growth was concentrated in the smaller sized metro
areas. The steady growth of the largest, that is, greater
than 5 million population, MSAs, from 1980 to 2000, is
now eclipsed by the increasing growth rate of the smaller
sized MSAs. This is partly a function of reclassification as
smaller urban areas become classified as MSAs but also
perhaps indicative of a greater spread of economic activity
and population down the hierarchy of MSAs.
Table 2 lists the twenty largest MSAs from 1950 to 2010.
Notice the stability at the very top of the hierarchy with New
York, Los Angeles, Chicago, Boston and Philadelphia and San
Francisco keeping their position in the top ten over this 60-
year period. There is also change as Sunbeltmetro areas enter
the top twenty. There were six metro areas in 2010 that were
not part of the top twenty in 1950—Atlanta, Dallas, Denver,
Orlando, Sacramento, and San Juan. The inclusion of San
Juan, in Puerto Rico, now involves a wider definition of the
“national” urban system than one restricted to mainland
USA.
3. Central Cities
The metropolitan region can be divided into central city and
suburban areas. The most significant feature of the last sixty
years is the suburbanization of the US population. In 1950
only 23 percent of the US population was living in suburbs.
This figure increased to 46.8 percent in 2010. The central city
population has remained relatively fixed at around one-third
of the entire population. In 2010 it was 36.9 percent.
The story of the central city of MSAs is complex. Short
and Mussman (forthcoming) plot the individual trajectory
of the population size at each successive Census since 1900
of the top 100 cities and identify four model types. The
first type of city is steady decline. A typical city in this
category is Detroit that experienced a peak of 1.84 million
around midtwentieth century and then continuous decline;
its 2010 population was 713,777 down from 951,270 in
2000. The city embodies the rise and rapid fall of the older,
underbounded, industrial city. Other cities in this category
include Akron, Baltimore, Birmingham, Buffalo, Cincinnati,
Cleveland, New Orleans, Rochester, Toledo, and Pittsburgh.
In these cities the loss of employment caused by the long slow
decline of manufacturing is yet to be replaced completely
by new forms of economic growth. These cities also bear
the brunt of an urban fiscal crisis as the steady loss of
population and tax base erodes the revenues of the city. The
second type of city is continuous increase. Here the story
is of rising economic and population growth and ease of
annexation. A typical case is San Jose, CA, a Sunbelt city
with an expanding economy based largely on information
technology. In 1950 the city population was only 95,280,
but by 2010 it was 945,942. Decades of spectacular growth
fueled in particular by the Silicon Valley boom in hightechnology
and computer-related industries make San Jose
one of the most prosperous and economically dynamic cities
3
4
5
6
7
8
9
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Population (millions)
Decade
Figure 1: Population of New York City.
in the country. In 2010, San Jose’s median household income
was 50,046. The city was also able to annex territory,
increasing its area size from 17 square miles in 1950 to 177 in
2010. Other examples of this type include San Diego, CA, Las
Vegas, NV, and Orlando, FL. The third model type is growth
interrupted. Here examples include New York City (NYC),
Atlanta, San Francisco, and Seattle. These cities’ upward
population trajectory saw some decline before returning to
growth and eventually surpassing their previous population
peak. Figure 1 plots the trajectory of New York City where
the population was relatively flat from 1950 to 1970 before
a 20-year decline and then resurgence after 1990. The city’s
areal size remained constant at 303 square miles from1950 to
2010. In Atlanta, there was rapid growth from 1950 to 1970
followed by 30 years of decline before population began to
up tick again after 2000. In the case of Seattle, population
peaked in 1960 then declined before growth returned by the
1990 census. The city was the same size in 2010—84 square
miles—as it was in 1960. In this category some annexations
did occur, but, especially for the large cities of Atlanta, New
York, San Francisco, and Seattle, population growth within
stable boundaries was the most important process.
Then there is the slowly resurgent city, where previous
peaks are not reached, but there is a slow steady return
of population. Examples include Boston, Philadelphia, and
Washington, DC. In all three cases the areal size of the city
remained roughly the same. Washington DC’s population
peaked in 1950, then saw continuous decline until 2000
at which point the city’s population began a decade-long
resurgence. Cities of this type are big urban areas that did not
reach the free fall of continuous decline nor the pronounced
returned upward trajectory of the growth-interrupted cities.
These cities show signs of population recovery, if not quite
to past peaks, at least a bending of the curve from decline
to upswing. And in most cases, population growth was not
simply the result of city annexation of suburban territory.
The four categories are model types, and there is some
overlap between the categories. Chicago, IL, for example,
lost considerable population from 1950 to 1990, gained over
100,000 between 1990 and 2000, then lost 20,000 between
2000 and 2010 all against a background of fixed areal size
since 1960. It falls between steadily declining and resurgent
city categories. Other cities in this same liminal categorical
space are Philadelphia, PA, and St. Paul, MN. Some cities
are located in the continuous growth category despite some
International Journal of Population Research 3
Table 1: Percentage of US population in metropolitan areas
(MSAs), 1980–2010.
MSA size 1980 1990 2000 2010
Over 5 million 20.4 21.1 29.9 24.6
1 up to 5 million 25.2 28.9 27.6 29.5
Up to 1 million 29.2 27.5 22.9 29.5
Nonmetro areas 25.2 22.5 19.6 16.4
Total 100 100 100 100
small reductions from 2000 to 2010; these include Hialeah,
FL, St. Petersburg, FL, Santa Ana, CA, and Tulsa, OK.
Some of the causes of population resurgences include
the growing concentration of high-paying professional jobs
in central cities, shrinking US household size that makes
suburbs less attractive choices compared to central cities,
changing immigration patterns as streams of foreign-born
migrants move to central cities. Mikelbank [1, 2] highlights
some of the trajectories of change within metro regions and
between suburban places. Declining crime rates also make
central city living a more attractive proposition. There is also
a marked uptick in commercial and residential reinvestment
in selected central city areas. Selected central city areas are
being revalorized as capital and people move back to the city.
The relative position of individual cities is shown in
Table 3 that lists the relative size of the largest 20 cities
from 1950 to 2010. Two trends can be noted. First, the
relative stability of the very largest cities of New York, Los
Angeles, Chicago, and Philadelphia that remain within the
top ten. Second, the reshuffling of the top twenty as the older
industrial areas such as Cleveland, St. Louis, and Buffalo
drop out and the more rapidly growing Sunbelt cities such
as Houston, San Antonio, Houston, Dallas, and San Jose
enter. From 2000 to 2010 three more Sunbelt cities entered
the top twenty: Fort Worth, Charlotte, and El Paso. And
two rustbelt cities—Baltimore and Milwaukee—dropped
out. The changes in rankings embody deeper economic
restructuring in the US economy and the associated rise and
fall in urban fortunes.
4. Suburban Areas
The suburban spread of population continues across the
country. Between 2000 and 2010 most MSAs added suburban
counties to their metropolitan region. The Pittsburgh MSA,
for example, added Armstrong County with a population
of 68,941. More dynamic MSAs significantly extended their
metropolitan range of influence even further. Atlanta MSA,
for example, added 8 new counties with a combined population
of almost 160,000 and total area of 2,250 square miles.
The suburban frontier continues its outward movement
turning even more of the US landscape into a metropolitan
society.
There is considerable variation within the category of
suburbs [1]. Hanlon et al. [3] describe the US suburbs as a
place of disparate and divergent realities. At one extreme is
what Lang and LeFurgy [4] describe as boomburbs that they
characterize asmunicipalities of more than 100,000 that were
not the major city of their MSA and experienced double-digit
growth for three consecutive decades. Remember, however,
that the data reflects different definitions of municipalities.
Using 2000 data these authors identified 54 boomburbs
with a combined population of 8.9 million. Using the same
criteria but updated with 2010 data, only 31 boomburbs were
identified with a combined population of approximately 6
million. The rate of red-hot growth has dipped as economic
recession, and housing market collapse has undercut very
rapid suburban growth. Even the experience of particular
boomburbs has slumped since the housing market collapse.
Flagler County in Florida, part of the Palm Coast MSA,
grew an astonishing 92 percent between 2000 and 2010, a
function of the housing boom of 2001–2007. Since 2008
however the housing market has collapsed with rising
unemployment and foreclosure rates. The poverty rate in
the country has increased by almost fifty percent from 2000
to 2010, from 11.3 percent of all persons to 15.1 percent.
Across the metropolitan landscape, the growth in the former
boomburbs has stalled due to the housing crisis.
At the other extreme, there is also what Hanlon [5]
describes as “suburbs in crisis.” These are defined as suburbs
that witnessed population loss and economic retrenchment.
Her analysis was based on 2000 data. We can get a more
recent snapshot by updating the story of just one of these
suburbs. Dundalk, an industrial suburb in the Baltimore
MSA, experienced increased poverty and declining income
from 2000 to 2010. The poverty rate for individuals increased
from 9.2 percent to 12.4 percent in 2010, while the median
household income fell from 45,088. The older
industrial suburbs continue to decline.
Over the past half century, the suburban experience has
diverged. The difference between rich and poor suburbs has
substantially increased. In the past decade the rapid growth
of boomburbs has deflated due to the housing crisis and the
difference between rich and poor suburbs widens as poverty
continues to rise in the poorer suburbs.
5.Megalopolis
We can consider some of the changes within metropolitan
areas by considering one case study. One of the largest
contiguous areas of metropolitan counties is what Jean
Gottmann [6] first identified as Megalopolis, a region
spanning 600 miles from north of Richmond in Virginia
to just north of Portland in Maine and from the shores of
the Northern Atlantic to the Appalachians. A profile of the
region from 1950 to 2000 was undertaken by Short [7]. The
region now includes the consolidated metropolitan areas of
Washington-Baltimore, Philadelphia, New York, and Boston
and covers 52,000 square miles. In 2000 the population
of this giant urban region was 40.6 million. By 2010 it
has increased to 44.6 million with in situ growth and new
counties being added because of spreading metropolitan
influence. It is the single biggest metropolitan concentration
of population. In both 2000 and 2010 it contained just over
14 percent of the entire US population.
4 International Journal of Population Research
Table 2: The twenty largest metropolitan areas in the US by population, 1950–2010.
Rank
1950 1970 1990 2000 2010
MSA name MSA name MSA name MSA name MSA name
1
New
York—Northeastern NJ
New York, NY New York (CMSA)
New York, NY
(CMSA)
New York, NY (CSA)
2 Chicago, IL
Los Angeles/Long
Beach, CA
Los Angeles, CA
(CMSA)
Los Angeles, CA
(CMSA)
Los Angeles, CA
(CSA)
3 Los Angeles, CA Chicago, IL Chicago, IL (CMSA) Chicago, IL (CMSA) Chicago, IL (CSA)
4 Philadelphia, PA Philadelphia, PA
Washington, DC
(CMSA)
Washington, DC
(CMSA)
Washington,
DC/Baltimore, (CSA)
5 Detroit, MI Detroit, MI
San
Francisco/Oakland,
CA (CMSA)
San
Francisco/Oakland,
CA (CMSA)
Boston, MA (CSA)
6 Boston, MA San Francisco, CA
Philadelphia, PA
(CMSA)
Philadelphia, PA
(CMSA)
San Jose/San
Francisco/Oakland,
CA (CSA)
7 San Fran/Oakland, CA Washington, DC Boston, MA (CMSA) Boston, MA (CMSA)
Dallas/Ft.Worth, TX
(CSA)
8 Pittsburgh, PA Boston, MA Detroit, MI (CMSA) Detroit, MI (CMSA)
Philadelphia, PA
(CSA)
9 St. Louis, MO Pittsburgh, PA Dallas, TX (CMSA) Dallas, TX (CMSA) Houston, TX (CSA)
10 Cleveland, OH St. Louis, MO Houston, TX (CMSA) Houston, TX (CMSA) Atlanta, CSA
11 Washington, DC Baltimore, MD Miami, FL (CMSA) Atlanta, GA (CMSA) Detroit, MI (CSA)
12 Baltimore, MD Cleveland, OH Seattle,WA (CMSA) Miami, FL (CMSA) Seattle,WA (CSA)
13
Minneapolis/St. Paul,
MN
Houston, TX Atlanta, GA (CMSA) Seattle,WA (CMSA)
Minneapolis/St. Paul,
MN (CSA)
14 Buffalo, NY Newark, NJ
Cleveland, OH
(CMSA)
Phoenix/Mesa, AZ
(CMSA)
Denver, CO (CSA)
15 Cincinnati, OH
Minneapolis/St. Paul,
MN
Minneapolis/St. Paul,
MN (MSA)
Minneapolis/St. Paul,
MN (MSA)
Cleveland, OH (CSA)
16 Milwaukee, WI Dallas, TX San Diego, CA
Cleveland, OH
(CMSA)
St. Louis, MO (CSA)
17 Kansas City, MO Seattle,WA St. Louis, MO San Diego, CA Orlando, FL (CSA)
18 Houston, TX Anaheim, CA Pittsburgh (MSA) St. Louis, MO San Juan, PR (CSA)
19 Providence, RI Milwaukee,WI San Juan, PR (CMSA) Denver, CO (CMSA)
Sacramento, CA
(CSA)
20 Seattle,WA Atlanta, GA
Phoenix/Mesa, AZ
(CMSA)
San Juan, PR (CMSA) Pittsburgh, PA (CSA)
Bold denotes new to the top twenty. CMSA: combined metropolitan statistical area. CSA: combined statistical area.
Within this region three trends can be noted from 2000 to
2010. First, the urban core regions have retained their relative
demographic position. In 2000 the combined population of
Boston, New York, Philadelphia, and Washington was 10.64
million and by 2010 this increased to 10.88 million. All these
cities had established producer services, while Baltimore,
with a relatively large manufacturing base, declined from
651,154 in 2000 to 620,961 in 2010, reflecting the broader
continuing shift of the dynamics of the US economy away
from manufacturing to producer services.
Second, suburban dominance continued as the percentage
of the regions’ total population increased from 72 to 74
percent. Compared to earlier decades, however, the central
city-suburban distribution now seems more stable as the
years of rapid suburban growth and central city decline are
now replaced by a more varied picture of resurgence in
selected city centers with a leveling off in rapid suburban
increases. There are still areas of rapid growth especially
in the southern part of Megalopolis that includes counties
fringing the Washington Baltimore MSAs. Loudon County
in the northern Virginia suburbs of the Washington MSA,
for example, saw an absolute increase from 169,599 in 2000
to 312,311 in 2010. Elsewhere in this particular growth
region, rapid growth slowed. Howard County, Maryland,
for example, saw a huge population increase from 23,110
in 1950 to 247,842 in 2000 but only a slight increase to
287,085 by 2010. The growth was effectively a filling-in
of the commuting corridor between Washington DC and
Baltimore.Many of the former high growth suburbs are now
built out. Throughout the region there was also evidence of
decline in some of the older inner suburbs, what Puentes and
Warren [8] describe as first suburbs. In Essex County in New
International Journal of Population Research 5
Table 3: Twenty largest metropolitan cities in the US by population, 1950–2010.
Rank
1950 1970 1990 2000 2010
City name City name City name City name City name
1 New York, NY New York, NY New York, NY New York, NY New York, NY
2 Chicago, IL Chicago, IL Los Angeles, CA Los Angeles, CA Los Angeles, CA
3 Philadelphia, PA Los Angeles, CA Chicago, IL Chicago, IL Chicago, IL
4 Los Angeles, CA Philadelphia, PA Houston, TX Houston, TX Houston, TX
5 Detroit, MI Detroit, MI Philadelphia, PA Philadelphia, PA Philadelphia, PA
6 Baltimore, MD Houston, TX San Diego, CA Phoenix, AZ Phoenix, AZ
7 Cleveland, OH Baltimore, MD Detroit, MI San Diego, CA San Antonio, TX
8 St. Louis, MO Dallas, TX Dallas, TX Dallas, TX San Diego, CA
9
The Age of Adolescence
No full textChildren, LiteratureThe Age of Adolescence
Ellen Handler Spitz
Jepp, Who Defied the Stars
by Katherine Marsh
Hyperion, 385 pp., $16.99
THIS PAST SUMMER, with a transfixed ten-year old by my side, I stood in Madrid’s palatial Museo Nacional del Prado, face to face with Diego Rodríguez de Silva y Velázquez. We gazed at the self-portrait of this grand master of the bravura brush stroke, gripping his palette in his left hand and wielding a paintbrush in his right, and we admired the wasp-waisted five-year-old Infanta Margarita who poses pertly before him in the endlessly fascinating Las Meninas. I pointed out diminutive King Philip IV and his queen, caught in their black-rimmed mirror just left of a coffered door, which opens mysteriously onto a dazzle of light. But about the court dwarfs—Maria Bárbola, with her bulbous head and short arms, and Nicolasito Pertusato, who kicks the lazy mastiff—I had little to say. A barrage of earnest questions from the child beside me exposed a glaring lacuna in my art history background. Why are they there? What are they doing? Were they servants, too? Why did the Spanish court keep them?
As a girl, Katherine Marsh was similarly mesmerized by the dwarfs in Velázquez’s masterpiece, and by those that appear in other paintings of the period. To explore their plight, she conceived Jepp, Who Defied the Stars—her latest venture into books for young readers. Jepp is a first-person narrative, an historical novel set in the Spanish-ruled Netherlands of the late sixteenth century and in Denmark. Permit me a sigh of discontent that Las Meninas is nowhere to be found between the covers of her book, for its reproduction would have served as a model for the way that works of visual art can spark literary creation. This very painting, after all, inspired Oscar Wilde’s heartbreaking tale of an Infanta who laughs a little dwarf to death on her twelfth birthday.
Throughout Jepp, Marsh’s well-imagined title character and her other court dwarfs provide answers to some of the questions raised by Las Meninas. After a happy childhood in a village near Utrecht, Jepp arrives at the Spanish court of Coudenberg in Brussels to become a court dwarf. He is brought there by a strange courtier, Don Diego (who later proves to be Jepp’s absent—and deceased—father’s younger brother). At fourteen, the boy is no taller than he was at seven.
In Brussels, the Infanta treats Jepp and his cohort handsomely, but rather like toys or pets. She expects them to amuse and divert her, but they are not regarded as fully human. Courtiers and servants shamelessly touch their bodies ad libitum, costume them at will, and make them suffer a host of indignities (Jepp’s first is to jump out of a pie served to the Infanta). Far more horrifyingly, a delicate blond dwarf named Lia, Jepp’s friend, is victim of a secret rape by a courtier named Pim. Lia persuades Jepp to accompany her in an attempted escape so as to bear her baby in freedom, but she dies in childbirth.
While it successfully conveys the degradation to which the dwarfs were subjected historically, the inclusion of this dark episode in a book for young readers may expose some pre-teens to an excess of depravity. Before her violation, Lia enjoys a close friendship with Robert, a kindly Hagrid-like giant who is also retained by the Infanta as a grotesque, and the court immediately assumes that it was he who made her pregnant. Marsh’s florid evocation of this huge male copulating with this tiny female, even though it proves false, may seem to corroborate widespread childhood fantasies of sexual acts as aggressive conquests.
Eventually Jepp is banished from the Infanta’s presence, and his story continues while he is en route to another castle, Uraniborg in Denmark; he is transported there from Brussels in a cage reminiscent of the contraption occupied by the outsized Lemuel Gulliver in Brobdingnag. The latter parts of Marsh’s novel find him under the aegis of the famous astronomer Tycho Brahe, an eccentric island-dwelling, silver-nosed scientist, whose beer-guzzling moose attends dinner in his castle. Jepp is made to eat on the floor under the table at Tycho’s feet.
What makes all this particularly poignant in the context of “young adult” fiction is that Jepp and his cohort—diminutive persons who appear neither adult nor child—can so easily stand in for the book’s intended readers. Suffering extreme humiliation, Marsh’s characters not only teach historical injustice but, closer to home, they mirror the manipulation, objectification, and failure to be taken seriously that many teens and pre-teens feel they endure under uncomprehending adults. The dwarfs in Marsh’s novel, moreover, are propelled by their frustrations into unproductive behaviors: at Coudenberg, one preens constantly before a looking glass, and another is addicted to hippocras. Under conditions of oppression, their relations with one another are tarnished by rivalry and suspicion.
Thus the dwarfs become, in Marsh’s skillful hands, supremely sympathetic figures. In pre-adolescence, our bodies morph, betraying us day by day. Alien to ourselves as well as to others, we yearn to shoot up instantly or to stop growing altogether—to shrink back into warm childhood, where right and wrong lay neatly folded in separate piles on a shelf. But the door to childhood is shut. Adolescents are newly encased—like Jepp—in bodies that seem too small (or too large) but never a match for what is inside them, which nobody else can see. Marsh’s characters capture many near-ubiquitous experiences of this particular stage of life. Jepp exists in relative emotional isolation: his body, psyche, and surrounds feel intermittently out of sync.
Features of Marsh’s plot parallel with psychological acuity deep levels of pre-adolescent experience. Haunted in a fatherless household by the mystery of his paternity, Jepp longs to find his father. The desire to find one’s true, lost parents animates, as we know, not only the fantasy lives of youth who have endured bereavement, abandonment, and adoption, but also of many a discomfited teen. During much of Marsh’s story, Jepp narrates his adventures while traveling like a small animal in a cage. A rough keeper named Matheus tosses in his daily food, and he knows not his destination. Again, modern echoes abound: despite the plethora of insignificant choices accorded them, young people’s lives are not in their hands, and they often feel cooped up in prisons not of their making. Marsh’s doubled narration (Jepp reminiscing about Coudenberg on his way to Uraniborg) mirrors the way youth balks haltingly at the regimentation of cultural clock time (alarm buzzers, class bells), their jerky back-and-forth between outer and inner worlds captured so brilliantly by Bill Watterson in his Calvin and Hobbes comic strips. Marsh evokes this wonderfully, with all its puzzling confusion. As one reads Jepp, Who Defied the Stars, present and past entangle just as childhood and adulthood spar.
Over the course of this fine novel, what matters principally is that a meek, naïve boy, easily manipulated and duped to the point of endangering himself and his friends, develops—despite his handicap—into a more mature character, capable of assuming responsibility for his choices and responding finally to the devotion of a fiercely independent young woman. Jepp progresses from adoration of frail Lia to love for Magdalene, the daughter of Tycho Brahe, who is not a dwarf. In an image that reverses the Robert-Lia fantasy, Magdalene towers over Jepp, and from her he learns the necessity of accepting fate while acting “out of love rather than fear.”
Caught between worlds, Jepp not only grows up, he becomes real. He exits forever the world of Las Meninas, but this time with life and with hope.
Ellen Handler Spitz is Honors College Professor at the University of Maryland (UMBC). Her most recent book is Illuminating Childhood. She writes regularly about children’s literature for The Book
Making English Grammar Meaningful and Useful Mini Lesson #4
No full textHelping Verbs, English GrammarThis lesson was developed by John Nelson and Tymofey Wowk, 2012
Making English Grammar Meaningful and Useful
Mini Lesson #4
Helping Verbs – 5 Grammatical Functions
The purpose of this lesson is to list the ways in which Helping Verbs are used in English tenses.
English is not a heavily inflected language. Instead, it makes use of Helping Verbs. Helping Verbs are verbs that have grammatical functions in subject-verb combinations without adding semantic meanings to the sentences in which they are found. Chart #1 presents the helping verbs used in the 12 English tenses.
Chart #1 – English Helping Verbs
Simple
Tenses
Continuing
Tenses
Before
Tenses
Continuing
Before Tenses
Future
Tenses
will
will be
will have
will have been
Present
Tenses
do
does
am
is
are
have
has
have been
has been
Past
Tenses
did
was
were
had
had been
In spoken English, Helping Verbs are frequently reduced and contracted with other words, but they have 5 very important Grammatical Functions.
1. Helping Verbs indicate the Kind of Tense used in an utterance. Continuing Tenses use the verb ‘BE’ as helping verbs. Before tenses use the verb ‘HAVE”. Simple tenses use the verb ‘DO’ in negatives and questions.
2. Helping Verbs indicate the Time – Past, Present or Future – when the events described by the verb took place.
3. English Negative utterances are formed by placing the word ‘NOT’ after the initial Helping Verb as illustrated in Chart #2. Frequently the Helping Verb and ‘NOT’ are contracted.
This lesson was developed by John Nelson and Tymofey Wowk, 2012
Chart #2 Using Helping Verbs in Negative Sentences
Simple
Tenses
Continuing
Tenses
Before
Tenses
Continuing
Before Tenses
Future
Tenses
I will not walk home.
I will not be walking home.
I will not have walked home.
I will not have been walking home.
Present
Tenses
I do not walk home.
I am not walking home.
I have not walked home.
I have not been walking home.
Past
Tenses
I did not walk home.
I was not walking home.
I had not walked home.
I had not been
walking home.
4. English Questions are formed by inverting subject-verb word order. In nearly all cases, it is a Helping Verb that comes before the subject to form a question as illustrated in Chart #3.
Chart #3 Using Helping Verbs in Questions
Simple
Tenses
Continuing
Tenses
Before
Tenses
Continuing
Before Tenses
Future
Tenses
Will you walk home?
Will you be walking home?
Will you have walked home?
Will you have been walking home?
Present
Tenses
Do you walk home?
Are you walking home?
Have you walked home?
Have you been walking home?
Past
Tenses
Did you walk home?
Were you walking home?
Had you walked home?
Had you been
walking home?
5. English requires sentences to have Subjects-Verb Agreement regarding singularity and plurality. In most instances, it is the Subject and the Helping Verb which must be in agreement
Making English Grammar Meaningful and Useful Mini Lesson #12
No full textDependent Clauses, Phrases, Adjective Clauses, Noun Clauses, Adverb Clauses, English GrammarThis lesson was developed by John Nelson and Tymofey Wowk, 2012
Making English Grammar Meaningful and Useful
Mini Lesson #12
Clauses and Phrases: The Difference is Simple
The purpose of this lesson is to explain the difference between Dependent Clauses and
Phrases, and to present the three basic kinds of Dependent Clauses.
A Clause is a group of words that go together to form a unit. It has one essential characteristic; a
Clause must have a Subject-Verb Combination. A Phrase is a group of words that go
together, but which does not have a Subject-Verb Combination.
Sentences are composed of at least one clause which gives a complete idea. Dependent Clauses
are those that do not communicate a complete idea. They are connected to an independent clause
in some way. English has 3 kinds of Dependent Clauses. Each does the same thing as a
particular part of speech and, therefore, each is named for a part of speech. There are Adjective
Clauses, Noun Clauses and Adverb Clauses.
Adjectives describe nouns; Adjective Clauses also describe nouns. However, adjectives
generally come before the nouns they describe, while Adjective Clauses follow the nouns they
describe. The following sentence contains both an Adjective and an Adjective Clause. They
each describe the noun ‘man’.
He is the young man who you met yesterday.
Nouns are used as Subjects or Objects of sentences. Noun Clauses are also used as Subjects or
Objects of sentences. These two sentences contrast the use of a Noun and a Noun Clause. Both
are objects of the sentences in which they are used.
The teacher asked a question
The teacher asked if the students understood.
Adverbs indicate time or reason among other things. Adverb Clauses indicate the same
information. These two sentences contrast the use of an Adverb and an Adverb Clause.
He did his homework late in the evening.
He did his homework after he came home from the party.
This lesson was developed by John Nelson and Tymofey Wowk, 2012
ELLs will find it helpful to contrast Dependent Clauses with similar Phrases. The following
sentence pairs illustrate these differences.
An Adjective Clause and an Adjective Phrase:
I met the man that teaches the grammar class.
I met the man teaching the grammar class.
A Noun Clause and a Noun Phrase:
He asked me if I would help him study.
He asked me to help him study.
An Adverb Clause and an Adverb Phrase:
The game was cancelled because it rained.
The game was cancelled because of the rain.
ELLs find Clauses and Phrases confusing and mysterious, but they do not need to be. Learners
can be taught to recognize and produce word groups with and without Subject-Verb
Combinations. Once this is mastered, competence using these 3 kinds of clauses and phrases is
more easily accomplished. Understanding their basic constructions and relating them to simple
parts of speech will enable ELLs to produce Dependent Clauses and Phrases easily and use them
accurately
Making English Grammar Meaningful and Useful Mini Lesson #14
No full textAdverb Clauses, English GrammarThis lesson was developed by John Nelson and Tymofey Wowk, 2012
Making English Grammar Meaningful and Useful
Mini Lesson #14
Adverb Clauses: Don’t Use Future Tense
The purpose of this lesson is to describe Adverb Clauses and illustrate a few characteristics of
their use.
Adverb Clauses provide information about the Main Clause of the sentences in which they are
found. They are the only kind of Dependent Clause that is not a part of the Main Clause. They
can be found either before the Main Clause or after it. There are a few important aspects to
learn about them.
Adverb Clauses and Adverb Phrases have several meanings, which are illustrated in the
following chart. Notice the differences in some cases between the CONNECTORS used with
Adverb Clauses and those used with Adverb Phrases.
Meanings of Adverb Clauses and Phrases
Meaning Adverb Clause Adverb Phrase
Time The game was played
after it stopped raining.
The game was played
after the rain.
Reason The game was not played
because it rained.
The game was not played
because of the rain.
Purpose The game was delayed
so that the field could dry.
The game was delayed
in order to let the field dry.
Contrast Both teams came to the game
although it rained.
Both teams came to the game
in spite of the rain.
Since Adverb Clauses are not found within the Main Clause, they can be found either before it
or after it. All of the sentences in the chart above could be expressed with the Adverb Clauses
and Phrases coming before the Main Clauses. When an Adverb Clause precedes the Main
This lesson was developed by John Nelson and Tymofey Wowk, 2012
Clause, it is preferable to put a comma between the Adverb Clause and the Main Clause.
When the Main Clause comes first, a comma is not needed because the Adverb Clause
Connector indicates the beginning of the Adverb Clause. (For example, notice the 3 commas
in the preceding sentences.)
Adverb Clauses have one characteristic that ELLs need to be made aware of. The Simple
Future Tense cannot be used in an Adverb Clause when the clause expresses a future time. The
Simple Present Tense or the Present Continuing Tense is used instead. Note the following
examples:
1. Tomorrow, he will drive home. Tomorrow, he will wash his car.
2. Tomorrow, he will drive home and he will wash his car.
3. Tomorrow, he will drive home and wash his car.
4. Tomorrow, after he drives home, he will wash his car.
5. Tomorrow, he will drive home before he washes his car.
All the examples in these sentences will take place tomorrow. When the two ideas are presented
in separate sentences, as in example 1, they employ the Simple Future Tense. When they are
combined by a Simple Connector, as in sentence 2, the Simple Future Tense is used with both
clauses. Even in Sentence 3, where the Simple Connector connects phrases, the Simple Future
Tense is used with both verbs. However, Adverb Clauses are used in both sentences 4 and 5.
Notice that the Simple Present Tense is used in both Adverb Clauses in both sentences despite
the obvious future meaning of the clauses. Future Tenses cannot be used in Adverb Clauses of
time
SEMANTICALLY RICH, POLICY BASED FRAMEWORK TO AUTOMATE LIFECYCLE OF CLOUD BASED SERVICES
No full textManaging virtualized services efficiently over the cloud is an open challenge. Traditional models of software development are very time consuming and labor intensive for the cloud computing domain, where software (and other) services are acquired on demand. Virtualized services are often composed of pre-existing components that are assembled on an as-needed basis. We have developed a new framework to automate the acquisition, composition and consumption/monitoring of virtualized services delivered on the cloud. We have divided the service lifecycle into five phases of requirements, discovery, negotiation, composition, and consumption and have developed ontologies to represent the concepts and relationships for each phase. These are represented in Semantic Web languages. We have developed a protocol to automate the negotiation process when acquiring virtualized services. This protocol allows complex relaxation of constraints being negotiated based on user defined policies. We have also developed detailed ontologies to define service level agreements for cloud services. To illustrate and validate how this framework can automate the acquisition of cloud services, we have built two applications from real world scenarios. The Smart cloud services application enables users to determine and procure the cloud storage service that matches most of their constraints and policies. We have also built a VCL broker application that allows users to automatically reserve the VCL Image that will best meet their requirements. We have developed a framework to measure and semi-automatically track quality of a virtualized service delivery system. The framework provides a mechanism to relate hard metrics typically measured at the backstage of the delivery process to quality related hard and soft metrics tracked at the front stage where the consumer interacts with the service. While this framework is general enough to be applied to any type of IT service, in this dissertation we have primarily concentrated on the Helpdesk service and include the performance rules we have created by mining Helpdesk data
EFFECTS OF DISTURBANCE AND A DOMINANT CONSUMER ON STREAM COMMUNITY ASSEMBLY: EXPERIMENTAL AND OBSERVATIONAL EVIDENCE
No full textWithout understanding changes in aggregate and compositional properties, it is possible to misinterpret mechanisms driving community variability. Changes in patterns of variability can be caused by independent and interactive effects of biotic and abiotic drivers. In an experimental study, I manipulated the presence of a dominant detritivore (P.gentilis) and disturbance (drying). I found that disturbance lowered aggregate variability and the presence of P.gentilis lowered compositional variability, but only in the absence of disturbance. In an observational study, I created an index describing relative likelihood of disturbance (system-level drought) for multiple watersheds and tested the impacts of the likelihood of disturbance and the presence of P.gentilis on aggregate and compositional variability. Disturbance tended to increase aggregate variability and decrease compositional variability, but only in the absence of P.gentilis. The results of both studies indicate that there may be an interaction between biotic and abiotic drivers that can significantly change community dynamics
Should Head Start Centers Have Naps? An Experimental Study Examining the Effects of Nap Policy on Classroom Behavior in Preschool Children
No full textAs preschool teachers and administrators strive to meet academic standards and make school schedules as efficient as possible, they differ in their opinions and approaches to daytime naps. To some extent these differences reflect a lack of authoritative data on how naps affect classroom and learning behaviors. The present study is the first known experimental study to directly examine the effects of eliminating naptime on preschool children's behavior. In general, results were mixed. Behavioral observations in the classroom indicated no significant differences in children's behavior and even suggested some improvement in behavior after naptime cessation. Teacher and parent reports, however, indicated that children's inattention increased after nap elimination. One explanation for disparate results may be that negative effects of nap cessation emerge later in the school day and/or at home, though one must consider study limitations before confidently reaching this conclusion. Exploratory analyses revealed that children slept less overall after nap elimination, though there was some evidence suggestive of increased nocturnal sleep efficiency. This efficiency may in part explain children's lack of differences in observed disruptive behavior and irritability after nap elimination. The present study highlights the need for future studies to examine the effects of naptime cessation utilizing objective behavioral assessments at school and at home as well as instruments to examine sleep architecture
Cell Response to Hydrogel Tissue Scaffolds
No full textTissue Engineering is evolving as one of the most promising therapies in regenerative medicine. Biomaterials are attractive substrates for tissue-engineering applications because they are biocompatible, can be biodegradable, and can be fabricated from a variety of materials. The ideal biomaterial substrate mimics native extracellular matrices to regulate cellular function, provide physical structure, and allow the diffusion of vital solutes. Cell morphology, proliferation, and differentiation are linked to substrate geometry and physical properties. We show that the dimensionality (2D vs 3D) of a substrate more strongly influences neuronal morphology than substrate stiffness. We also correlated GRGDY-modified alginate gel composition with gel stiffness and cell behavior: increased GRGDY and alginate concentrations resulted in increased gel stiffness and density of adherent cells. While increased calcium also increased gel stiffness, cell density was optimal at an intermediate calcium concentration. This work adds towards our understanding of optimizing scaffold properties to direct cell response
