By Lambert Strether of Corrente.

Lambert here: I’ve updated the post by adding an additional comment under Figure 2, and added Figure 3.

This is the third in a continuing series of worksheets, in which I seek to understand and document the institutional structure of the Democratic Party, so-called, by looking carefully at the challengers in a sample of key races that are must-wins for the Democrats if they are to take back the House (part one; part two). I should emphasize that this is not a horse-race approach, although with more data we may converge on some conclusions about the consequences of a Democrat victory, if not about the likelihood of victory itself. In my previous approach, I looked at two questions: Whether militarized candidates — not merely former (?) intelligence types, but law enforcement types as well law enforcement having become militarized — were a significant presence in my sample, and whether outside groups — Emily’s List, Our Revolution, etc. — were. In each case the answer was yes.

This post builds on that previous effort. To the coding for militarized (“MILO”) candidates and party faction (whether Democrat “regulars” or outside groups) I have added coding for occupations in sciences, health, and education (“SHE”)[1] and support for #MedicareForAll (coded with “➕”)[2]. By intersecting MILO, SHE, party faction, and #MedicareForAll support, I hope to understand divisions in the party better. The coding is documented in the Legend beneath the Table.

My approach was the same as before: I went through each state, district, and read each candidate’s bio (updating as I went; PA-05 was especially colorful, even for Pennsylvania). Based on the bios, or if necessary Google search, I coded the candidates for “SHE” status and #MedicareForAll support.[3] I present the results in Table 1, and then provide interpretations in Figures 1 and 2. So you can skip right over the table if you want! (I’ve got to say, though, that I find this material fascinating. “What is government itself,” asks Madison, “but the greatest of all reflections on human nature?”)

Table 1: Worksheet on House Races, Election 2018 (2018-04-02).

Biography: m, i, l, o (“MILO”) Military,Intelligence, Law Enforcement, Other); s,h, e (“SHE”) Science, Health, Education

Backers: BN, EL, IN, JD, OR; DCCC; DP; S: Brand New Congress,Emily’s List, Indivisible, Justice Democrats, Our Revolution; DCCC; Democrat Party, whether elected, staffer, official, etc.; inspired by Sanders.

Policy: [➕]; Medicare for ALl.

First, the the totals (and readers know my arithmetic is not always of the best, so do check me). From the “Dem Challengers” column, we have 113 total candidates. However, we are intersecting MILO, SHE, party faction, and #MedicareForAll support, and 20 candidates (!!) have left so little trace of themselves in BallotPedia or the Intertubes that they cannot be coded for using of those four factors. So we throw them out — they’re ineffectual anyhow — and are left with 93.

Now let’s look at #MedicareForAll support and opposition by party faction. To create Figure 1, I threw those candidates coded “➕” into one bucket and those not so coded into the other. Then I removed their names, and all the fancy formatting. Candidates who were only coded for “➕” became “?”. (“Michael Hepburn [JD; e] [➕]” becomes JD;e]. It’s occurred to me that if this project gets too much bigger, I might need to dust off my SQL skills). Then I arranged the results by party faction with the largest faction sorted first.

Figure 1: Division within Democrats on #MedicareForAll by Candidates

8 [DP][DP][DP][DP][DP][DP][DP;lm][DP;m] 5 [JD;e][JD;m][JD;m][JD][JD] 3 [EL;DCCC;DP][EL;DP;lm][EL;DP] 3 [S;s][S][S] 1 [S JD OR;DP;e] 1 [BN JD;m] 1 [OR;e] 14 [e][e][e][i][i][s][?][?][?][?][?][?][?][?] TOTAL 36 supporters 30 [DP;DCCC][DP;S][DP;e][DP;e][DP;h][DP;h][DP;i][DP;l][DP;l][DP;m][DP][DP][DP][DP][DP][DP][DP][DP][DP][DP]... 8 [ELIN;h][EL;DCCC;e][EL;DCCC;lm][EL;DCCC;m][EL;DP;m][EL;h][EL;l][EL] 1 [IN;l] 1 [DCCC] 17 [e][e][e][e][e][h][l][l][l][l][lm][mi][s][s] TOTAL 57 opponents

Some comments:

1) 36 of the 93 (31%) support #MedicareForAll; this is considerably less then the general population (depending, of course, on how the question is asked).

2) By far the largest number of #MedicareForAll supporters (14) are “average Joes or Janes,” unsupported by any faction.

3) The second largest number of #MedicareForAll opponents (17) are “average Joes or Janes,” unsupported by any faction.

4) By far the largest number of #MedicareForAll opponents (30) are Democratic apparatchiks, whether elected or otherwise (30), although there is some Democrat support for #MedicareForAll is well. (See especially TX-23, where both candidates in the runoff support it, and the colorful PA-05, where RIchard Lazer, who is (dare I say it) a machine pol, not that there’s anything wrong with that, support it.

5) Emily’s List is agnostic, although it supports #MedicareForAll candidates only when they are also party-affiliated (3).

6) DP and the BN/JD/OR//S (Brand New Congress, Justice Democrats, Our Revolution, Sanders-inspired) have only one case overlap.

Now, let’s look at #MedicareForAll support by occupation. I began with the same buckets as before (36 and 57), threw out the party factions, and resorted by occupation. (Where a candidate’s only affiliation was party, I replaced DP/DCCC/DNC etc. with “p,” occupation politician. I represented an unknown occupation by “?”) To review the Legend for Table 1, MILO is “military, intelligence, law enforcement, other,” and SHE is “science, health, and education.” Hence, of #MedicareForAll supporters, 10 have unknown occupations (first line), 8 are politicians (second line), 6 are “education” (third line), 6 are “military” (fourth line) and so forth.

Figure 2: Division within Democrats on #MedicareForAll by Occupation

10 ?????????? 8 pppppppp 6 eeeeee 6 mmmmmm 2 ii 2 lm,lm 2 ss TOTAL 36 supporters 22 pppppppppppppppppppppp 8 llllllll 8 eeeeeeee 6 mmmmmm 5 hhhhh 2 lm,lm 2 mi 2 ss 1 i 1 ? TOTAL 57 opponents

Some comments:

1) Because (a) MILO is evenly split (6 “military” supporters, and 6 opponents), and (b) SHE is almost evenly split (for education, 6 vs. 8, and science, 2 and 2) we can infer that occupation does not correlate with a candidate’s support or opposition to #MedicareForAll, with one significant expection: All the “h” (health) candidates oppose it.[4]

2) The political class opposes #MedicareForAll; 8 of 30 (26%) support it, a smaller proportion than all the candidates, which is in turn smaller than the general population.

NEW 3) By contrast, the 10 challengers without known occupations all support #MedicareForAll, and necessarily from outside the political class; this is an impressive degree of entry and engagement, and an indication that conventional wisdom outside the political class diverges from that within it.

NEW Now let’s sort our data by state[5], from greatest proportion of support to least. Candidates who do not support #Medicare for all are coded with “X”; those who do, with “➕.”

Figure 3: Division within Democrats on #MedicareForAll by State

TX ➕➕ 2/2 (100%) AZ XX➕➕➕➕ 6/8 (75%) CA XXXX➕➕➕➕➕➕ 6/10 (60%) WA XXX➕➕➕ (50%) 3/6 MN XXXXXX➕X➕➕➕➕ 5/12 (41%) NV XXXXXX➕➕➕➕ 4/10 (40%) FL XXXXX➕➕➕ 3/8 (37.5%) NH XXXXXX➕➕ 2/8 (25%) PA XXXXXXXXXXXXX➕➕➕➕ 4/17 (23.5%) NJ XXXXXXX➕➕ 2/9 (22%) VA XXXXXX➕ 1/8 (12.5%)

Some comments:

1) TX: It’s amusing to see the establishment-backed leader try to steal the left’s clothes on policy, and encouraging to see that they didn’t try the “universal health care” or “Medicare Extra” scams. Next, they’ll pass it and take credit!

2) CA: I can see why support would be so strong; a campaign by National Nurses United; a single payer bill introduced, though sidetracked by the dominant Democrat faction; experience with Covered California, which shows if it shows nothing else that government can actually deliver services, even using a Rube Goldberg device like the ObamaCare marketplace.

3) AZ: This surprised me; what’s going on in Arizona? Readers?

Conclusion

Assuming this sample is at all representative, it seems clear that the key barrier to support for #MedicareForAll in the Democrat Party is, well, Democrats. That is, the Democrat nomenklatura, those whose primary identity is as an elected, a staffer, or an official. Their support (26% in Figure 1) is disproportionately small, whether contrasted to liberal Democrats (64% for “single payer,”[6] says Pew), to the general population (52%), or to the 31% for all challengers. One might almost imagine that some mysterious, unseen body — perhaps one of Thomas Ferguson’s “industrial sectors”? — was exerting an unseen, almost gravitational pull on the party. The views of the “h” candidates — physicians being themselves an industrial sector — give credence to that view. On the other hand, #MedicareForAll is moving ahead strongly in California, even Texas, and surprisingly in California. It’s also clear that support for #MedicareForAll really is coming from the grassroots.

NOTES

[1] I should have been more exhaustive and added coding for small business people and corporate executives. Perhaps next time.

[2] The cross denoting a hospital or medical care; the best I could do with Unicode, unfortunately.

[3] I did not update for Outside Group support unless it was mentioned in the candidate’s bio; time pressed.

[4] I did not code for this, but in all cases the “h” candidates are physicians, and not nurses.

[5] The totals for Figure 3 differ slightly from the totals in Figures 1 and 2 because they are based on a hand count when I proofread the post again today. There are two more #MedicareForAll supporters, and five more candidates (I threw out too many). The discrepancy is not material with respect to the comments. Fiddling with bits of text is error prone, sadly.

[6] “Medicare for All” polls better.