Day 2--Mixed Results

Day 1--Time logged, 1:22

So day 1 started pleasantly enough--my old files booted up just fine in my shiny new copy of STATA 13, which appeared to be running super fast on my new computer.  After a couple of quick sort-resorts to remind myself I hadn't forgotten everything, I dove back into my first research chapter.

My dissertation looks at a group of approximately 425 districts that were following court-ordered desegregation plans at the time of the Dowell ruling in 1991.  I wanted to see how these districts fared throughout the 90s and 00s, particularly those that were released from court order.  My first chapter really looks at two questions in particular:

1. How did racial composition of districts under court order change relative to the overall public school population?
2. Did desegregation decelerate/resegregation occur in districts that were released from their court-ordered plans.

So I set off for Google Scholar to look for some resources that would help me start doing the analysis to answer these questions...and boy did I come across one.

For those of you who don't know Sean Reardon (all of you?) he's like Michael Jordan/Paul McCartney/Picasso of quantifying segregation using various metrics.  And he essentially worked with some other folks to answer my first set of dissertation questions in 2012--while I was still screwing around raising a 1-year old and traveling to recruit schools into a massive randomized control study for work.

Here's the good, the bad, and the ugly about finding this paper:

The Good

1. The paper confirms that my data set was pretty spot on--I'm going to compare mine to theirs (they dropped all districts with fewer than 2000 kids, I dropped only those below 500), but it looks like we pulled from all the same sources.
2. Reardon and his co-authors shows a few different ways to measure changes in districts from the time they were released from court orders.
3.  The conclusion to the paper specifically calls out a few of my other research questions as areas that warrant further research.

The Bad

1. I feel like writing this chapter is pointless now.  Reardon and his co-authors do a very sophisticated, detailed look at how the gains in desegregation achieved under court orders do indeed receed after those orders are listed.  It's really thorough and well done--to the point that I emailed my advisor a copy of the paper along with a plea to consider dropping this question and moving straight on to my other two questions.  He replied that if our data sets are different, it's worth writing this up. I'm going to take one more look tonight and hope that they are different.  If not, I'll soldier through, but if feels pointless, and though I'll give full credit to Reardon and his crew and admit that I'm basically replicating his research, it feels a bit like plagiarizing.  At the very least, I feel like I've already read the ending of the mystery I was planning to write.

The Ugly

I'm not going to say I'm totally lost trying to follow the "discrete-time hazard models" and "comparative interrupted time-series models", but...uh, this is significantly more complicated than running a basic linear regression.  Stata (and Google! And whatever versions of "Advanced Statistical Modeling for Dummies" I can find, don't fail me now!)!

So--at least I have a somewhat clearer (if complicated) path in front of me.  Time to slog on and put my hour in for the night...why do I know it's only an hour?  Because last night, our youngest decided he wanted to wake up and hang out with us from midnight until 2. So yeah, short night for me.