Quantifying the School To Prison Pipeline -- a high level analysis of discipline-based inequities America's Public Schools¶

Introduction¶

America's 96,000 public schools provide the foundation for the next generation's education and, ultimately, future success.

Yet, educational researchers and practitioners worry that America's public schools do not provide all students equal opportunity for future success.

Some stakeholders feel the inequitable treatment of students is so severe -- particularly poor and minority students -- they've coined the term School to Prison Pipeline. That is, some schools and students are pushed, not to success, but towards the criminal justice system.

Overview of Investigation Foci¶

This analysis' following 3 questions will center on exploring this prominent and debated concept of "The School to Prison Pipeline" in US schools, generally defined as the disproportionate tendency of minors and young adults from disadvantaged backgrounds to become incarcerated, because of increasingly harsh school and municipal policies.

Discussions of "The School to Prison Pipeline" and its causes largely center on a few interrelated factors:

1. Disproportionate suspensions, particularly towards black and disabled students.
2. Police Presence on campus, especially in contrast to lack of counselors and mental health professionals, meaning troubled students may be more likely to be received by law enforcement than counselors who are trained in helping students cope, reform, and stay in school.
3. "Zero tolerance" policies in schools increasing suspension and expulsion rates as schools deliver harsh discipline for even first-time or relatively minor offenses in an aim to stop disruptive behavior before it gets worse.

We'll explore these key factors via desegregated data on all 96,000 US public schools from the 2016/15 school year CRDC data. Because revealing causality in these factors is impossible to determine given just this data, this investigation centers on the extent and nature of these key measures at a national level.

Overview of the Dataset¶

The Civil Rights Data Collection, school-level data for 2015-2016¶

The Civil Rights Data Collection (CRDC) is a biennial survey required by the U.S. Department of Education’s (Department) Office for Civil Rights (OCR) since 1968. (Note, however, that survey content changes over time.)

The 2015–16 CRDC (the most recent year published) collects data from all public local educational agencies (LEAs, ie School Districts) and schools, including

• long-term secure juvenile justice facilities
• charter schools
• alternative schools
• and schools serving students with disabilities

with a response rate of 99.8% from 17,337 LEAs and 96,360 schools. Specifically, I will be looking at the finer-grained data disaggregated by school.

Data content and format¶

Each school (row) in the dataset includes 1,800 columns (typically a student count disaggregated by race and gender for some school measure) regarding 32 general topics, comprising a 460 MB csv. The topics I will investigate utilize only 50 columns pertaining to suspensions, expulsions, and school population. I will only look at white, black, and hispanic students, who form the majority of students at nearly all schools.

Known issues with dataset¶

• From the CRDC report: "An important consideration for response rates is that the reporting process requires all schools and LEAs to respond to each survey item on the CRDC. Some LEAs, that did not have complete data, reported a zero value. It is not possible to determine all possible situations where this may have occurred. As such, it may be the case that the item response rates may be positively biased. For the large majority of CRDC survey items, the rate of missing data ranged from 0-5% of reported values."
• In the separate Data Prep notebook, IDs in the original dataset greater than 10 significant digits had been cast to scientific notation format and stored as strings. I recreated the IDs for those, which are a combination of State, local, and school identifiers.
• CRDC does not provide Lat Long coordinates, so I merged in school Lat Longs from the National Center for Educational Statistics in the Data Prep notebook. When schools did not have lat-long coordinates available, I assigned them the coordinate of their school district (LEA) office.

Load All Schools Data (after downlaoding)¶

Find this data in this Google Drive Folder.

Geographic distribution of all schools¶

To get a sense for the geographic distrubtion of the 96,000 schools, we can plot their lat-long coordinates. Schools are colored simply by their latitude.

Note Alaska and Hawaii faintly on the left, with lower population densities.

Analytic Questions¶

Question 1: How disproportionate are suspensions across race and gender?¶

What percentage of each demographic population recieve suspensions?¶

How many times more likely to be suspended are blank and latino students than white students?¶

For the above "percent of population affected" plots, it's near impossible to compare the severity across a single school. One way to zero on on this is to color schools by how much more likely a certain population is to be affeced compared to the least affected population. This measure might reveal schools where, even if a demogrpahic is severely affected, so were other demographics.

How likelyhood comparisons are calculated:

Percent of X pop affected / Percent of White counterpart population affected

Question 2: What impact have "Zero-tolerance" policies had on expulsion?¶

All analysis look at "students without disabilities expelled on zero tolerance policy".

Zero Tolerance policies impact 2% of white students, but about 4% and 5% of black and latino students, respectively, for schools who gave out at least one Zero Tolerance based expulsion for that demographic.¶

Question 3: Does the proportion of Campus Counselors (psychologists) vs Campus Police Officers correlate with suspensions?¶

Data notes:¶

1. It's possible to have fractional staff recorded if they are not full-time.

2. A Data entry, system-level error on the form filled in by schools caused only 22,000 schools (after corrections 25000) to correctly enter the number of Law Enforcement Officers on campus. Where this system error occurred, the value is -9. Due this fact, there are only 17,500 schools with both Police and Counselor counts. We'll do investigate Juvenile Justice Facilities seperately: first, because we'd expect different counselor and police presence there, but second because none of them actually recorded the number of police.

3. Where are the police data?¶

Notably, none of the 608 Juvenile Justice facilities which have a count enterered for Police officers. This may be because the police staff at JJ facilities do not map to the categories on the survey.

We could try to use Security Guards as a proxy for Police. However, only 64 of the 608 JJ facilities have data for both Counselors and Security Guards, so we've removed all JJ schools from the following analysis.

Non Juvenile Justice Schools:¶

Long Term Suspensions correlate with Police Presence¶

Plotting Campus Police against Campus Counselors per student, and color schools by we see a a hotspot of suspensions at shcools with low-counselor levels and high police levels.

You can also see how schools seem to hire with a predetermined ratio in mind: consistent ratio lines jut outward, most notably one marking the a 1-to-1 ratio.

This supports existing intution in the "School to Prison Pipeline" concept -- schools with high suspension rates confront troubled kids with police with higher likelyhood than trained counselors. However, it remains unclear if high levels of suspension-worthy activity triggered hiring more Police, or if increased Police (and a lack of counseling) escalate suspension counts.

Which leads us to two questions we can investigate: do Police correlate positively alone with suspensions, or does it worsen when mixed with low counseling?