Thread by @ThyConsigliori

25 September 2020 #BetweenTheLilneDotVote Analysis

ANNOUNCING our 2nd Tranche of Data!

In a word, as it stands (more on that in a bit) our BTL data is 100% the opposite of all the published polling you see in the news. If our data is right, everyone else is wrong.

2) Before we dive into the data above, allow me to share, again, our 1st tranche of data. I'll briefly explain the difference between the two below.

3) The BTL Algorithm is the difference. Our 2nd tranche benefits from it, our 1st did not. Here's the quick story. By July 29, we had collected enough data that I felt it was important to share. There was, however, a severe problem with the data. It was sample-bias skewed.

4) Our data was SO Trump leaning, that it was simply NOT possible to believe in it. My theory was that, as I am such an ardent Trump supporter, the people participating in our poll were influenced by and accessible to me, personally. So, obviously, a massive Trump bias, right?

5) Still, I couldn't throw my data away. Not only was it too hard fought in order to gain, I refused to believe it didn't have value. So, I worked and worked. At first, I broke my brain over the math, and I got nowhere. Here's what I did...

6) I used my intuition to explode Biden support and reduce Trump support with the following goal. What I wanted was an equal influence from all 3 groups, Democrats, Independents, and Republicans. The logic is simple.

7) If you have too many Republicans participating in your poll, as we at BTL do, you have to INCREASE the impact of those Democrats who have been so kind as to offer their votes. Hoping to give their voice an equal impact on our poll's outcomes, I simply increased its count.

8) The result was the chart you see above. I did NOT claim it to have the slightest scientific basis, and I don't claim that, for it, now. It was just the data I had, and I did the best with it that I could. What arose, though, had a serious impact we must turn to now.

9) The BTL model, our data model, couldn't be more simple. We work with our data to effect equality among three groups, Democrats, Independents, and Republicans. Simply 33% for each. We intend, in the future, to alter this model, once we build our own model of America's voters.

10) I hope you'll work with me on this. We're starting out with simple equality of impact. To do this, we have to expand the impact of those whose numbers we have the least. Since we have the least Democrats, their vote must have the largest increase in impact.

11) In our 1st tranche, I simply did that by instinct. What that means is this. I looked at the numbers and I - with no other mechanism than my own personal guess work - gave the most impact to Democrats, more impact to Independents, and I left the Republican count alone.

12) After publishing our 1st tranche, the game was on. What I knew I'd need was an algorithm. I started out with nothing, and built the algorithm from scratch. It's taken me these many weeks to do so. My algorithm works. It is proprietary, so I won't tell you much about it.

13) I am both happy and honored to tell you this much. What I did, instinctively, with the 1st tranche of data, my algorithm now performs with pure mathematical simplicity over our 2nd tranche, and will do so for all our work moving forward. It equalizes impact.

14) The algorithm is sensitive and easily can accommodate various different models. We can easily change the parameters for the model, off its current equal 33% basis. So, if we come to believe there are more Democrats, fewer Republicans, etc., we can change it like so...

15) Imagine our data informs us that America really does have 39% Democrats, 42% Independents, and only 19% Republicans, we can easily shift our parameters to reflect that count. One thing that we PROMISE, is that our model will ALWAYS be published.

16) And by "published," I do NOT mean in the fine print somewhere that you have to be dedicated to find. Right now, the model is 33% each for Ds, Is, and Rs. No, that is NOT our actual sample. More about that below. But it IS the actual impact on our projections.

17) I know. Promises are cheap. On that very note, I report - not promise - that our data is presented with the actuality of equalized impact by the three political identifications, and we have the algorithm to ensure it.

18) Now we return to our 2nd tranche, published for the first time above. Here's that chart, again. A question jumps to mind. If we've equalized the impact of our smallest contingent, Democrats, and our next smallest, Independents, then why such a Trump dominance?

19) Truth is, I was SHOCKED when our algorithm spat out data that looked almost exactly as my instinctively processed data had. I truly expected the two campaigns to be far closer together. I was, in fact, disappointed when Biden's numbers showed up so low.

20) A theory was born. Republicans are virtually united behind Trump. That's not news. In our data at BTL, Independents are breaking for Trump about 8 out of 10. If we're reflective of the nation's Independents, that should be - but won't be - news.

21) Imagine. What if our data is correct? I'm not saying it is. I'm only asking the hypothetical. What if our data is right, as to the break in the Independents' vote? If 8 out of 10 Independents break for Trump, he wins in a landslide. 80%? Can that be possible?

22) Let's talk about the art of the possible in polling for a moment. It explodes my brain every single time a reporter says:

This X percentage of Americans feel thusly...

No.

This X percentage of those polled here, feel thusly...

Do you see the difference?

23) A poll is a guess. If we've sampled our people correctly, and if their opinions as stated reflect all of America correctly, then, our poll indicates that this percentage of Americans feel like so.

You don't have to say those words.

You do have to have that humility.

Interim.

I need a break for this reason. My data truly does come in the context of inspiration from 2016's Dornsife Poll. I never fail to give them recognition. We'll be making that tie next, and I have to meditate on that for a bit.

Back soon...

24) An historical approach always grounds us. Why did Dornsife correctly call the 2012, and 2016 elections? I believe the answer is to found in the method they used, back then, but have now rejected. Back then, they used ONLY 3 questions.

23) Their 3 questions were:

1) Will you vote?
2) For whom?
3) Who will win?

Forgetting their sample - it was flawless back then! - and focusing solely on these 3 questions, you see perfect genius at play. I will never forget my emotion when I discovered those questions in 2016.

24) That Dornsife has abandoned its previous format breaks my heart. In 2012 and 2016, they were by far the strongest polling outfit in the world. Those 3 questions were the very basis of that domination.

25) I'm about to show 5 of their charts. You can't know about these charts unless you dive deeply into the content they provide. They're hidden in plain view.

They are:

1) Democrats
2) Lean Democratic
3) Independents (No party affiliation)
4) Lean Republican
5) Republican

26) These 5 charts answer a single question:

Who, in your state, do you think people will vote for?

That's a question! It follows perfectly from the Flynn Doctrine:

Who the people think will win, will win.

If you follow the Flynn Doctrine, then predicting winners is the job.

27) Dornsife's pure Democrats poll...

28) Dornsife's Lean Democrat poll:

29) Dornsife's Independent/No Party Affiliation poll:

(This the one that matters!)

30) Here's the Dornsife's Lean Republican numbers:

31) And here's Dornsife's break out for those who identify as Republicans:

32) The slightest examination reveals that even at Dornsife, they seek only the truth. I publish my advocacy, boldly. In polling, however, truth alone is the goal. If American Democrats have won the day, then we conservatives must bear the brunt.

32) If there's nothing else we ascertain from the above charts, we realize this.

Men interpret charts of data, the same way their illusions inform.

33) But perhaps we may glean a bit more. Perhaps, somewhere in the data, the truth lies. That is my prayer. That is my prey. I hunt the truth and will not stop until I bag it.

34) Please head over to our site, now. We ask the same questions Dornsife used to ask, but add two of our own. It appears we're the only out fit out there employing this method, this year. You'll find our 5 questions here:

BetweenTheLines.Vote

35) And you can count on our honesty, 100%, always. We state our position. We account for it. We fight the bias all human enterprises suffer. We seek the truth. Please join us!

Thread ends at #35.