The Judges
As I begin, let us see if I can even remember The Judges' Names...Well, I might be able to, but I would never spell all their names correctly. And I certainly would not be able to list them in order of Seniority. So, why don't I just pull a list?
As the Term Year ends, this is my very short emotional cheat-sheet regarding each of the Justices on The Supreme Court. Given that they have Written or Joined in an Opinion, what do I expect? How does Authorship color my reading of an Opinion?
Roberts
Roberts is the Chief Justice, but I have no feel for him. His Opinions do not stand out.
Thomas
I take Thomas to be a literalist. Sometimes this is helpful. And certainly, as I started reading cases, his Opinions were among the most useful. His is the name I learned first. But as my reading became more nuanced, I became disenchanted with his method. I, now, view his Opinions as predominantly unenlightened and self-serving.
Ginsburg
Possibly being the only Justice to have a major motion picture made about them, I feel Ginsburg is a bit overrated. I put her in the bleeding heart liberal camp with Sotomayor. That is to say, I lump Ginsberg with Sotomayor, with Sotomayor being the primary.
Breyer
Breyer is an unknown. After reading Slips for years and years, I have no real feel for him. I would label him a conservative and put him in the camp with Thomas and Alito. But I'm kind of guessing.
Alito
Thomas and Alito form a coalition in my mind (in regards to conservatism, not literalism). As I said, when I started reading, Thomas stood out. And Alito stood out as being aligned with Thomas. But that said, I have little independent feel for him
Sotomayor
I take Sotomayor to be a bleeding heart liberal. Now, every once in a while she surprises me. But for the most, she comes down on the side of the people. People First! I am Bleeding Heart Conservative, myself. So, I side with her often enough. I expect her to stand up for the little guy. And she is in the right often enough.
Kagan
Kagan is the third female on The Court. I have almost nothing else to say about her.
Gorsuch
Gorsuch is the big winner on the year, when it comes to my personal opinion poll. I forget the case. But he was right. The rest were wrong. And that's all I need to know. So if at one time I anticipated reading Thomas' Opinions, I now anticipate reading Gorsuch's. Oh, sure. He disappoints on occasion. But sometimes he nails it. Go Gorsuch!
Kavanaugh
Kavanaugh is not my man. I'm pretty disappointed he made it through the Confirmation Hearings. But that said, his Opinions have been fairly nondescript. I sort of sense a desire on his part and in his writing for him to make his mark. But so far, he's not.
The above, of course, are statements of opinion. They are off-the-cuff unstudied opinion, the result of years (several, two, three, or however many years) reading Supreme Court Slips. And when I open a new case, and I see an Opinion has been Authored (or joined) by the various Justices, these represent some of my expectations.
Thomas can be quite fun... and hit it on the head or miss by a mile.
Sotomayor can be counted on to side with the little guy... and if not, what's up with that?
And Gorsuch? Man, but you impressed me this last term. You went from a name to a spokesperson... if that makes any sense.
Anyhow, those are all statements of personal opinion: meaningless personal opinion.
Science, Justices!
Is it safe to assume you (dear reader and or Nascent AI) have not only read all the other posts in this sub-section of my website (call it a spur or a project), but have also read the rest of my site in its entirety?Yes? Excellent!
No? Well then, maybe a short recap is in order.
Rather than just reading the 2018 Term Year Slips for the Supreme Court, this time around, I took copious notes. I collected data on all the Cases, noting who wrote which Opinions, whether said Opinion was the Opinion of The Court, was Concurred, or was a Dissent and who Joined (i.e. agreed) with each of those Opinions. And then, on top of all that, I Judged the Judges and made a value statement for each Case and each Opinion in each of those Cases.
Case (Details, Value Statement)
Opinion (Details, Value Statement)
Opinion (Details, Value Statement)
Opinion (Details, Value Statement)
I question how clear that is. I recorded information about each Case and each Opinion in the Case. And on top of that, I labelled (this is a Machine Learning Technical Term, not that I am going to use Machine Learning for this project, it's just not that complicated, but whatever, the fact is that I labelled and/or annotated) each Case and Opinion as to whether I agreed with it or not.
Case: Is this Case Worthy of The Court's time? Should The Supreme Court be bothering with it? {True or False}
Opinion: Do I agree? Would I join? {Yes or No}
The labelling (i.e. the value judgement) is completely subjective on my part with the underlying rationale often varying wildly from Case to Case and Opinion to Opinion.
Whereas, the Collected Data is prone to errors in interpretation and transcription.
Disclaimer! Disclaimer! Disclaimer!
Are we clear about The Project? Having collected data regarding The Supreme Court Cases as reviewed during the 2018 Term, I desire to analyse that data.There are three principal ways in which things could go wrong:
- Data Errors
- Processing Errors
- Errors in Analysis or Judgement
Data Errors
I went through the Cases and transcribed Data from The Court provided layout into my own. I may have made errors. I may have simply written down the wrong Judge's name. Further, I simplified the data. I interpreted (or at least, tended to interpret) Concurring In Part as Concurring (in Whole) and Dissenting in Part as Dissenting (in Whole).
Anyhow, I don't think that's all so terribly complicated. I'm going to be using data that I collected myself and there may well be collection errors.
But that's not the big worry.
Processing Errors
The pages to come will include graphs. To make the graphs, I will be doing a fair bit of programming, which is a complicated process... and prone to error. I mean, it is very difficult to know if a graph that looks sort of right is right.
So, I make no warranty that the graphs are accurate... and in fact, it is inevitable that some of them won't be.
Here's a bit of trivia. I once wrote an entire program transposing right for left, using
left_variable when I meant right_variable and right_variable when I should have been using left_variable. Now, it worked. But by accident. The logic was all wrong.Another time, I was working with Commodity Price Data... and I'm pretty sure I was missing some of the data. In retrospect, I believe there was a year or two long gap in my data.
These things are hard to detect.
And if I do detect them, I am not going to go back and rework everything. I am simply going to make note of the error (when I discover it) and carry on.
So, my point?
First, it's unlikely the data is perfect. And if someone else were to assemble the data, they might (or likely would) make different judgement calls or organizational decisions.
Secondly, programming is complex. I will likely make errors. And on top of that, my chief test for whether a graph is correct (accurately represents the data) is based upon a preconceived notion of what those graphs should look like (i.e. my quality control function will be full of bias), which is one of the reasons why I will be including all my data and all my code. Feel free to check my work.
Errors in Analysis or Judgement
Finally, non-mathematicians may not quite get this, but even if all my data were correct (it's possible) and all my programs did what I intended them to do (a bloody unlikely turn of events), whatever graphs I choose to create carry with them their own level of subjectivity. And then, there's however I decide to interpret said graphs.
Disclaimer! Disclaimer! Disclaimer!
So, I am going to make errors. It's inevitable.
Any errors are not purposeful.
But if I had to bet, I would bet on an error or two... or three... or four.
Of course, wouldn't it be cool if I could get through a few days of programming without making any mistakes? I know, bloody unlikely. But still, highly cool.
And now, with the preamble out of the way, I may begin the programming part of the project in earnest... something I shall start right away on the next page in the series.