Canada, Part 2: Stunning Revelations from DreamBot5

Canada, Part 2: Stunning Revelations from DreamBot5

If you haven’t seen the first article yet, it might help to quickly peruse that one first.

October 21st was a historic day for DreamBot runs, for it marked the first time a color would make the top rung of surging dream words. And of all the colors possible, what color was it?CanadaFake5

…Beige. As a consequence, I had to do a double-take when I heard the Canadian newscaster mention “BIEGE Corolla with no license plates…” in the Canadian shooter story:

“The CBC’s Evan Solomon says he later saw a beat-up, beige Corolla with no license plates parked about eight meters from the War Memorial on Wellington. It was surrounded by police, who told Solomon it was the suspect’s car.”



The Light Bulb Turns On…

So, now I have yet another descriptive word that spikes in the collective dreams just prior to this story. It’s not everyday that we see the color beige in a major mainstream story, and from our data, it’s not everyday we see a spike in the dreams with the word beige either. Call it a coincidence if you want, but it nonetheless sparked an idea…

All I could envision then was a graph with a series of spikes on it, showing how all the big words from this Canadian story all surged just prior to the event. I planned to do a quick article about how these dormant dream words just came alive in the days leading up to the Canadian shooting, and all the words just happen to describe this event very well.

But something else came into my email container at the same moment. On the surface, it seemed to have little relevance to my proposed article, but I thought I’d at least take a look: http://nodisinfo.com/ottawa-shooting-big-lie/

I scanned the text very quickly and then went for the pictures. Strangely, the phone camera that allegedly recorded all the video that day inside the parliament just happened to have identified several camera crews all operating and scurrying around before the police showed up.

The aforementioned article hypothesizes that the whole scenario was staged because how could news media (the guys with those huge bulky professional camera gear) already be present AND operational when the first responders haven’t even made it to the scene yet?!


With All the Other Spikes…

Okay, so we already have a slew of descriptive words that described the event (see previous article), so I thought I should gather a couple other words that might describe a false flag or fake media event to see if the collective dreams could verify or demonstrate the allegations made by the conspiracy article. I did just that, and here’s the resulting graph:


Yes, I agree…right now this graph looks irrelevant, insignificant; however, there are some real jewels in here, and I’ll walk you through those now.

First up, look at the grayed out area…Section A. Focus on the green line (“False”) and the red line (“Camera”). Although it’s not an ultra-tight correlation, the two lines do tend to go up and down at the same time (with exception of the “False” spike on 08/29 has no correlative spike in “Camera”). Other than that, the lines are surprisingly similar in the characteristics. So far, I wouldn’t call that predictive or correlative to our headline, but…

Now let’s remove the red and green lines and dedicate another chart for the other two words: “Fake Media.”


Even though it doesn’t look like it, the word “Media” (blue line above) is 10 times more alarming than our previous head-turning meme called “Mike” (i.e., the Canadian shooter’s name). We shall put those words together in a minute, but notice the word “Fake” (red line above but it’s also the yellow line in the graph below). It does the same thing that “Guardian” did in our previous article. It pops up first, descends, and then pops even bigger a day or two later. It’s a double pop pattern, which could be very easy to identify in our sea of dream words (see a comparison of Fake and Guardian below)


It’s true that Fake could be associated with just about anything, and by itself this word is absolutely useless to our story. However, it follows the same pattern as all our other descriptive words, especially with that double-pop pattern compared to Guardian.

Now “Media” is an entirely different story. This word started out completely dormant and then went blazing to the moon in two tiers. Thus, it managed to evade our radar because of this incremental climb (and thus we’ve adjusted our math a tad to better pick up these types of movements in the future).

In order to fully appreciate “Media,” we really need to see the old chart first. Notice how our main character in the Canadian shoot-em-up news story is named “Mike,” and thus the main character in our previous graph is the same….”Mike,” as indicated by the huge red spike.

Canada spikes2

Okay, so Mike looks extraordinary in terms of speed and magnitude of its ascent in the collective dreamscape. Now let’s add the word “Media” to the graph here (black line in the graph below), to demonstrate the monstrous meme that quietly developed without our awareness:


Who is the main character of our investigation now? Media. And in that same graph, notice that I listed all the words that pop up in the lower right. I listed them chronologically (i.e., in order of when they popped in the collective dreams). Reading straight down the list is rather meaningful: [the] media [reports that] Mike murdered a fake Army guardian [of the] royal [Canadian military and abandoned a] beige [vehicle].

Would be nice to see vehicle surging with “Biege” so that we know what that color is describing. It would also be nice to have “Vehicle” surging at the same time as Beige so that our sentence retains the same order. Well as luck would have it, we have exactly what is desired here. Not only is “Vehicle” surging with Beige, it actually made the same DreamBot run because it was surging at the exact same time! Not only that but we actually see a double-pop pattern with Vehicle…



Chronology of the Spikes

In what will be our last graph below, I wanted to show some more statistics we’re working on and how if we can identify these in the future. Once successful, not only will we be able to predict big events, but we’ll be afforded some underlying information about those events (such as “fake murder” or “Army guardian,” or “beige car,” etc.)


In this chart, we can see WHEN the spikes happen in relation to the news. For example, the light blue line (“Murdered”) spikes 12 days prior to the news.

We’ll also be looking at the TYPE of words and when they rise and fall in relation to the big news stories. For example, is there any coincidence that Mike and Barry both surge big-time 23 and 19 days (respectively) prior to their big international headline? The average of those two is right at 3 weeks (Barry was the corrupt rabbi we covered in an earlier article).

We’ll be looking at specific patterns and matching those up with timing as well. For example, “Fake” and “Guardian.” In the mainstream versions of the story, there’s obviously no evidence of “Fake,” but “Guardian” is probably the main piece to the headline. Therefore, should “Fake” also be given the same priority since it shows up with the exact same pattern at a similar time prior to the event?

Certainly, we can’t say with any type of certainty the answers to these questions. Only further testing, comparing, analysis, and vetting will give us a better idea for the ultimate truth here. However, what we do know is that there are quite a few coincidences here. Eventually, the coincidences might become too prevalent, which would only suggest that the collective mind does, in fact, see future events prior to them coming true. And yes, it would mean that the collective can see whether the event is staged or not!

By |2014-10-26T12:33:12+00:00October 26th, 2014|DreamBot, DreamStats, General News|6 Comments

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  1. cj October 26, 2014 at 7:16 pm - Reply

    Life is a learning process and what, or whom is of 100% perfection? I’d not be so quick to accept the attack of “blowing it”…

    Chris your work here is utterly amazing – just goes to show how one turns a negative into a positive – and not only did you do that, the learning scale was tremendous. I love it~@!!!

    • ndcadmin October 27, 2014 at 10:28 am - Reply

      Thanks for stopping in, CJ! Thanks for the compliment…means a lot, but it means even more coming from you!

  2. Duke October 27, 2014 at 7:20 am - Reply

    Some of us (perhaps many) can read what is written but has no idea of what your saying. Frankly with advanced degrees, I require your website produce a “Dreams for Dummies” book. Thank You
    I wish you would produce a dreams for dummies publication explaining just what your saying about dreams. I understand about 25% of whats written and most of that is how to join, and how to put in your dreams and then it stops! After that I become loopy trying to figure out what is being said.

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