Many people were scratching their heads Wednesday morning (or late Tuesday night), when we realized that South Carolina Democrats had nominated a literal “Some Dude” – an unemployed veteran living with his father – who somehow managed to front the $10,000 needed to run.
South Carolina State Senator Robert Ford weighed in on the matter later on Wednesday, remarking:
No white folks have an ‘e’ on the end of Green. The blacks after they left the plantation couldn’t spell, and they threw an ‘e’ on the end.
(If you’re wondering about the title, Gadsby is a 260-page novel that contains no instances of the letter E.)
Both Greene and Vic Rawl were relative unknowns and we’ll assume no voter knowledge of either candidate . Given the campaigning by both candidates (or lack thereof), I think this is a relatively tenable assumption.
So, let’s start at the county level – what’s the relationship between the percent of non-white registered voters and the percentage Greene received?
Here are two maps, with the non-white voter percentage on the left and Greene’s percentage on the right.
Is there a relationship? Maybe – hard to tell. Tom Schaller goes into this in more depth than I do.
However, thanks to the relatively good South Carolina State Election Commission website, we can go further to the precinct level. The geographic data for mapping precincts simply isn’t available, but we can still look at the numbers. (Sidenote: Absentees and provisionals can’t be attributed to a specific precinct and are tossed from here on out.)
Here’s a scatterplot of the non-white RV percentage and the percentage that Greene received on Tuesday and a simple regression line through it. Below that are the Stata output from a simple regression taking the non-white RV% as the independent variable.
The regression tells us two things:
- For every 1% increase in the non-white percentage of RVs, Greene’s percentage can be expected to increase 0.22%.
- For a hypothetical county with 100% white RVs, Greene’s expected percentage should be (!!) 51.6%.
But is the relationship there? Hard to say – it is statistically significant, but the R-squared is a measly 0.1425, meaning the other 85.75% of variance in Greene’s percentage is explained by something else.
Statistics disclaimer: Go ahead and skewer me for using a linear regression. (What else was I going to do?) I know the estimators here are going to be far from unbiased – that’s a picture-perfect example of heteroskedasticity if I’ve ever seen one…
I’m hesitant to rely solely on percentages though – there were plenty of precincts with few RVs and where few votes were cast (as you can tell by the 100% Greene precincts floating along the top edge). We can also consider this in terms of numbers: the number of non-white RVs and the number of votes for Greene in a given precinct.
Now, the regression tells a few things again:
- For every additional non-white voter, Greene’s vote count can be expected to go up 0.09. (Keep this in context of 24% voter turnout between both primaries!) This effect, again, is statistically significant, and very much so.
- For a hypothetical precinct with no non-white RVs, Greene will receive 7.8 votes.
- 62.6% of variance in Greene’s vote totals by precinct can be explained by the number of non-white RVs.
So again, is the relationship there? I think the second method presents a stronger case for the “E”-phenomenon than that first. But that said, is this instance of identity politics any more extraordinary than other instances? Does this have to do with voters having very little information (paging Scott Lee Cohen)? The second analysis, I might add, is also confounded in part by varying turnout across precincts…
Robert Ford may be on to something, but it’s all hard to say. (Lastly – if you haven’t realized the difficulty in writing with no Es, this post excluding Stata outputs, contains 438 of them.)
Last time I checked Ashley Greene (the model in the SoBe commercials) and State Representative Gerald Greene, a Democrat in my state of Georgia, are two names that popped up right away that are not black.
But “Greene” sounds “whiter” to me than “Rawl”.
Rawl brings singer Lou Rawls to mind.
That’s about 10 months of unemployment benefits.
…what do Simon, Theodore and Dave think about all this?
I can see it moving the needle by a few percent, in such a low-information race, but Greene won by a blowout (59-41).
If you don’t know anything about the candidates in a primary or non partisan race, LEAVE IT BLANK!
(Of course you probably won’t be reading SSP)
Dude fooled me for years. Thanks Robert Ford
Maybe South Carolina voters thought that Alvin is related to Jeff Greene, the multi-zillionaire businessman who is running to win the Democratic nomination for Governor of Florida.
… a gadfly of the first order. He supported keeping the Confederate flag on the statehouse (he’s black). On 90% of what he supports, he is a loner.
Nobody takes him seriously, which is why he did so poorly in the Governor’s race.
BTW, Rawl won the absentee vote statewide by a sizeable margin. I wonder if computer manipulation/malfunction was involved. I saw a documentary about Diebold once that comes to mind.
would be nice for someone to do a poll of people who voted in the Democratic primary and ask them who they voted for and why and how they heard of the candidate.
We always joke about the dead voting after the end of their natural voting lives, but I am curious how many dead people voted for a candidate that did not campaign.
Democrats went to vote in the primary. In a low information race with 2 candidates, the person listed on top/ first of the ballot got a lot more votes. I am going to run in Idaho Democratic primary for governor as AaaaaGomer Aaaaaa
From FiveThirtyEight: SC Democratic Primary Getting Weirder by the Hour.
http://www.fivethirtyeight.com…
I did some digging and found an SC-Sen poll conducted by PPP in late May. While PPP did not bother to poll the Democratic primary (why would they?) they did release figures on Rawl’s favorability with crosstabs for 2008 Vote. Using this data, I managed to do some back-of-the-envelope estimates of what could be expected in among a Democratic primary electorate voting between Rawl and an Unknown Candidate (I’m therefore ignoring the theory that there was any significant racial bias for Greene).
First the numbers: Obama voters gave Rawl a 6-18-76 favorability rating. I assumed that those who had a favorable opinion of Rawl would vote for him over Greene 98% of the time. For voters holding an unfavorable opinion of Rawl, I assumed a 90-10 breakout in favor of Greene. Finally among those who did not have enough knowledge to have an opinion, I gave a 53-47 edge to Greene, based mostly on ballot placement.
The results:
Favorable (6) – 98% Rawl, 2% Greene – 4.88 Rawl, 0,12 Greene
Unfavorable (18) – 10% Rawl, 90% Greene – 1.8 Rawl, 16.2 Greene
Not sure (76) – 47% Rawl, 53% Greene – 35.72 Rawl, 40.28 Greene
Estimated vote (100) – 43.4% Rawl, 56.6% Greene
Actual vote – 41.04% Rawl, 58.96% Greene
Obviously, theres a good deal of Margin of Error in my numbers and my assumptions. But I think the calculations do illustrate that it’s not a great leap to explain the results with Rawl’s lackluster favorability numbers. No need for conspiracy theories or accusations of shenanegans.
who voted for Greene why they voted that way?
significant at all, just like Tom Schaller. I don’t think it’s REALLY significant, my hypothesis would be that there is a small subset (25%)? of the AfAm electorate who knew who those guys are and broke mostly for Greene, and the others were distributed randomly.
And as for the second one, couldn’t you do another one controlling for precinct size?
Because it looks a little bit like you might just have found a relationship between precinct size and race. Which is interesting, but not in this context. Plus, it’s driven really much by the outliers in the upper right I guess (impact analysis?)
“Son, go make yourself useful doing something.”
“I don’t have anything to do!”
“Well, find something!”
several days pass…
“Hey dad, can I use this ten grand?”
“What’re you doing with this?”
“I’m filing to run for Senate.”
“You kiddin’ me?”
“No.”
“Well, then go right ahead.”
http://www.postandcourier.com/…
Now correct me if I am wrong, but political consultants aren’t known for working both sides of the aile.
Even if he was a plant, that would not be illegal by itself. I have seen numerous plants placed in primaries by both sides at the state rep and state senate level in Pennsylvania.
A prominent example was in the 50th State House Democratic primary this May. The incumbent Democrat is facing felony charges for public corruption and was facing a strong challenge from a county commissioner in the district. Then all of the sudden, some random union dude pops up and undermines the challenger. The random dude raised hardly any money and it was clear that his campaign was receiving help from the incumbent like the incumbent’s staff placing signs for both candidates in the public right of ways.
According to the File A Excel document linked from the Census page on surnames from 2000, people named Greene are 70% white, 26% black, whereas people named Green are 59% white, 36% black. Maybe things are different in South Carolina compared with the US as a whole, but it seems unlikely that the “e” at the end is really a signal of blackness.
If that was the plan, they’d have been much better with a candidate named Washington (90% black), Jefferson (75%), or Booker (66%).
This diary concludes that there exists a significant correlation between the % of non-white voters in a voting district, and the % of votes received by Greene, and therefore that Greene received preferential voting from non-white voters. It does so on the basis of a non-zero value for r^2 (presumably, Pearson’s r, the product moment correlation coefficient).
This is a mis-understanding of the meaning of r^2. r is a way of summarizing the strength of a correlation, when a correlation is already known to be significant. It is possible to have a high value of r^2 for completely uncorrelated numbers.
A related analysis is a Pearson analysis, which the significance level at which the null hypothesis of zero correlation is disproved (thus, a small probability indicates it is highly unlikely that there is zero correlation between two arrays. I perform such an analysis here:
http://www.dailykos.com/story/…
I conclude there is no evidence that non-white voters voted preferentially for Greene.