Read the report if you really want to know what this story is about.
http://www.annenberginstitute.org/pdf/JenningsPallasRpt.pdfsome very short snippets:
THE PROCESS: New York City is unique in that all students must apply to high school, and this admissions process is important
to understanding how new school foundings may have changed the distribution of students across schools. Over
the past twenty years, the number of public high schools in New York City has grown from about 120 schools
to over 400. Each year, more than 80,000 eighth-graders from public and private schools apply for entry into a
public high school program. The application process takes the better part of a year, beginning with open houses,
auditions, and entrance examinations; it concludes when student appeals are decided and schools’ final rosters are
created.
The application process is anchored in a simultaneous queuing process modeled after the hospital residency
“match.” Students list up to twelve schools (or school programs)* in their own order of preference, but the schools
do not know whether the student ranked the school first or twelfth. Schools rank-order applicants according to their
stated or unstated criteria; a complex computer algorithm is used to match students to schools. Students are ultimately
offered a seat at one school only. This process unfolds in three rounds. If a student is not offered a seat in the first
round, s/he can reapply to schools with open seats in the second round, and so on.
New York City schools use multiple admissions regimes to admit students. There are nine specialized high schools,
eight of which require a competitive score on an entrance exam, and one of which (LaGuardia High School) requires
an audition. Some school programs are screened, which means that selection is based on a student’s previous
record of academic performance and, in some cases, an interview; others, typically in the performing or visual arts,
screen students on the basis of an audition.
Programs admitting students through the “educational option” method select half of their incoming students on the
basis of their academic record, while drawing the other half randomly from applicants to the program. Unscreened
programs rely solely on a computer to randomly select students from applicants, and a student’s prior academic performance
is not allowed to be considered. “Limited unscreened” programs also rely on a random selection from
among applicants whom the school verifies have demonstrated an interest in the program by attending a school’s
information session. Other high schools in the city are “zoned,” which means that they admit students who live
nearby, whether or not they have applied to the school. All of the high schools in Staten Island and some of those
in the Bronx, Brooklyn, and Queens have a comprehensive zoned program, and many schools with comprehensive
zoned programs have specialized theme programs as well.
The majority of new small schools are limited unscreened. Admission to these schools is not based on students’ performance,
but on schools’ confirmation that the student is making an “informed choice” to attend the school. What
constitutes an “informed choice,” however, has been left to the discretion of individual schools. Some schools require
students to attend information sessions; in the past, schools have required that students attend a session with a parent
or guardian, but this practice has now been forbidden by the NYCDOE. Other schools have asked students to
fill out applications – some involving essay questions and recommendations from their middle school principal and
guidance counselor – to verify informed choice. In addition, until recently, all limited unscreened schools had access
to individual students’ prior attendance, grades, their test scores, their date of birth, their address, their sending junior
high schools, and their special education and English language learner status. Whether schools have used this
information to select their students remains an open question.
*An individual school in New York City may host multiple “programs,” often organized around curricular themes,
while some other schools only operate one program. Students apply to individual programs rather than to schools;
for example, if a school operates twelve programs, a student could list each of these programs as his or her twelve
choices through the school choice process.
****
NOTE: so students "apply" to particular programs or schools. One of the above para's implies that there is a possibility that some of the "small schools" MAY use some information inappropriately, but that is has not been determined.
In fact, it seems as if the "process" of applying itself is largely responsible for the skewed numbers.
****
Before introducing our findings, we first draw
attention to the geographic distribution of
small schools across the five boroughs of New
York City. Between the fall of 2002 and the fall
of 2008, 207 new schools meeting our sample
selection criteria (not transfer schools and with
data available on ninth-grade classes) had been
founded. Seventy percent of these schools are
located in the Bronx and Brooklyn, while 15
percent are located in Manhattan, 14 percent
in Queens, and 1 percent in Staten Island (see
Figure 1).
Are the students who enroll in new small schools
similar to students enrolling in other New York
City high schools in their boroughs?
We begin with the question of whether the composition of new small high schools differs from other New York City high schools in their boroughs.
Because new small schools are generally unscreened schools, which do not select their students based on prior performance, and schools in the comparison group include schools with competitive admissions based on prior performance, we might expect new small schools to enroll lower-achieving students on average.
. . . New small schools, on average, had entering classes
that were less likely to be proficient in
mathematics in eighth grade (a difference
of 6.1 percentage points) and less likely to
be male (a difference of 4.1 percentage
points). New small schools were also less
likely to enroll special education students
(a difference of 1.7 percentage points).
At the same time, new small schools enroll
students who are more likely to qualify
for free or reduced-price school lunches –
the conventional measure of a student’s
socio-economic status – a difference of
10.3 percentage points.
There are two caveats to these results. For the
four years for which data are disaggregated for
full-time and part-time special education students
(2002-2003 through 2005-2006), we
estimated the same models. We found no difference
in the percentage of students in parttime
special education in small schools. However,
we found that small schools over this time
period were substantially less likely to educate
full-time special education students, a difference
of 4.6 percentage points. During this time
period, small schools were given a waiver that
allowed them to exclude full-time special education
students until their third year of operation. However, we found that even for schools
that were open for three or more years, small
schools continued to serve a smaller fraction of
full-time special education students (a difference
of 2.9 percentage points).3
Overall, the story of the growth of new small
schools in New York City is complex. In some
ways they were more selective than other high
schools in their boroughs, and in other ways
they were not. We found no evidence, for
example, that the ninth-graders entering new
small high schools had better academic records
than the ninth-graders entering other high
schools, as indexed by rates of proficiency on
state reading and mathematics tests; in fact,
they had worse performance on prior mathematics
tests. Nor were the entering students in
new small schools economically advantaged as
measured by eligibility for free or reduced-price
lunch; these schools actually had higher percentages
of students eligible for free or
reduced-price lunch than did other New York
City high schools. At the same time, new small
schools were significantly less likely to enroll
ninth-graders who were male or full-time special
education students, and new small schools
that serve both ELL and non-ELL students
were less likely to enroll ELL students (NYIC
& ACNY 2006).
Do the characteristics of students enrolling in
new small high schools change over time?
We now consider how these differences
changed over the period 2002-2003 through
2008-2009.
. . . Each year thereafter <2004-2005>, small schools enrolled a
progressively more disadvantaged population. . .
. . . This result is consistent with the pattern of
school closings.6 It appears that as the first
round of large schools closed, students who
would have attended the closed schools initially
did not attend the new small schools. Over
time, as more and more large comprehensive
high schools closed, more academically challenged
students have populated the new small
schools.
. . .
Have New York City’s high school reforms altered
the distribution of students across schools?
One of the possible consequences of the
expansion of small schools is a shift in the distribution
of students across schools. The most
common way of thinking about student distributions
is racial/ethnic segregation, which is
generally tracked using the Index of Dissimilarity,
denoted as D. This index ranges from 0 to
1, where 0 represents an even distribution of a
minority group across schools, and 1 represents
the extreme case in which some schools are
entirely made up of minority students and the
remaining schools are entirely comprised of
majority students. The value of D can be interpreted
as the fraction of minority students who
would have to change schools in order for
them to be evenly distributed across all schools.
Thus, a value of 0 indicates that students are
already evenly distributed; a value of .5 indicates
that one-half of all minority students
would have to switch schools to create an even
distribution; and a value of 1 would imply that
all minority students would have to switch
schools to create a distribution in which the
same proportion of minority students was present
in all schools.
Although the focus of segregation is often the
distribution of racial and ethnic groups, in this
report we examine the evenness of the distribution
of several other student attributes
. . . A similar pattern is observed for the distribution
of students eligible for full-time or parttime
special education services, with higher
rates of segregation in Manhattan, the Bronx,
and Brooklyn than in Queens and Staten
Island. More than 20 percent of the special
education students in Manhattan, the Bronx,
and Brooklyn would need to change high
schools for these students to be represented in
equal proportions across high schools in these
boroughs.
****
NOTE: A whole lot of statistical information - lots of charts that I can't post here. If you are really interested in this subject and the REAL REASONS WHY this is happening - and no, it does NOT appear to be some nefarious deliberate attempt on the part of the schools - or Bill Gates for that matter!
*****
In conclusion:
But we still lack insight into
how and why students and their families
choose to rank some schools highly and to
ignore other high schools. A more detailed
analysis of the ways in which a student’s academic
background and needs, and where he or
she lives, shape high school choices could
enable the system to respond more effectively
to what parents and students deem to be
important.