Aug. 25, 2025

EP 131: Terrestrial and Sasquatch Data

EP 131: Terrestrial and Sasquatch Data
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Season 12

Terrestrial, the founder and analyst at the Sasquatch Data Project, joins the SE Crew to discuss Sasquatch and assorted findings!

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WEBVTT

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Views and opinions expressed by the guests that Sasquatch Experience

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do not necessarily reflect the opinion of the host, sponsors,

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or affiliates of the Sasquatch Experience. As always, listener discretion

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is advised.

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We got some one or something crawling around out here,

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and see what it was?

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Was it a person or an animal.

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Or I can't know. All I know that my underway

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came on and I get happened to Glenn and be

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the thing running across the head good bye man or something.

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To look by the men.

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I don't know what it was.

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Back in two thousand and five, we set out with

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one goal to give voice to the mystery and those

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who pursue it. Sasquatch Experience podcast has been your go

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to source for serious Bigfoot discussion, where we separate fact

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from folklore. Always grounded in research and respect. We've interviewed eyewitnesses,

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experts since Skeptic to Like because understanding Bigfoot isn't just

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about belief, It's about the journey. Nearly two decades later,

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we're still chasing shadows and sharing stories. The search never stopped.

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Welcome to the Sasquatch Experience.

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Hello, Get somebody out.

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Here, and here we go.

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Welcome to the Sasquatch Experience, everybody, Monday, August eighteenth, twenty

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twenty five. And what a great show we have for

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you all tonight. We've got a full house here as

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you can see down at the bottom. James Baker, vance

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Nesbitt our guest tonight, Terrestrial Henry May and Matt Arner

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from the Allegheny Plateau Project. Great show we're going to have.

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But before we kick off, just a couple of housekeeping notes.

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This weekend, Friday through Sunday is the twenty twenty five

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Pennsylvania Bigfoot Camping Adventure. Myself, Matt and James Baker. We're

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going to be there sponsoring doctor Jeff Meldrum, all representing

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Sasquatch Experience, and we'll be speaking at ten am on Saturday.

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So show up with your selected produce, which, by the way,

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if you're going to throw anything, make sure it's good

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so we can collect it. Or Squatch out Hunger, folks,

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Squatch out Hunger. We still need your help. We've kind

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of stalled in donations. We've got a lofty goal at

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twelve hundred and fifty bucks. We need you, so take

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a minute if you have the time. If you're so inclined,

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go to the website click on the banner to take

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you to Squatch out Hunger. It's a goal, that's it's

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a I don't even want to say it's a goal.

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It's a cause that's really important to us here at

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Sasquatch Experience. We do it every year. Help care about

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our neighbors a little bit and raise some money to

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take care of some folks in need. Every dollar equals

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ten meals through their formulations, so just remember that every

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dollar you donates helping to give ten meals to folks

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in needs. To go ahead and Sasquatch Experience dot com

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click on the banner for Squatch out Hunger. We need

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your help on that and for our patreons, which folks

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you guys, we don't need to remind you, but in

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case you're do, you can join for as little as

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get the fingers up boys two dollars a month. We

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missed our watch along last night because somebody took an

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unplanned early nap, so because of that we'll we spend there,

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of course rescheduling our watch along for another date. So

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you know, as aside from the watch along once again,

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I offer my sincerest apologies.

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For that.

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As little as two bucks a month, you get ad

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free shows. Mostly you get episodes of Cryptic Wilderness featuring

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Matt Arner and myself down there at times Baker's Hot Takes,

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which you really don't want to miss. And then the

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Sasquatch Experiences little short form podcasts where I go over

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some recent sightings and share them with you. So that's

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all I got for the news. Anything else from you

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guys before we kick off and I give our intro

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and we start the show thinking off, all right, guys,

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we've all been excited about this one, okay, ever since

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I stumbled upon the Sasquatch Data Project and some of

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the really great, you know, informational slides that she's put

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out there on Instagram. Terrestrial is the creator of the

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Sasquatch Data Project, an ongoing effort to provide researchers with

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Sasquatch report data and a format optimized for data analysis.

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She has a Bachelor of Science and Earth and Atmospheric

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Sciences from the Georgia Institute of Technology, and while in attendance,

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she played an integral role in categorizing, identifying, and measuring

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ground ice features on the Dwarf Planet series as part

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of NASA's don mission. In twenty twenty three, she began

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to development of the Sasquatch Data Project's data set. Her

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work primarily focuses on the application of statistical and NASA

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on reported sasquatch encounters, with particular emphasis of the regional

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variation of behavioral and morphological patterns of reported sasquatches, as

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well as investigating witness psychological responses and summing that up.

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We're just so pleased to have you on the show, Terrestrial.

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Thanks for joining us and putting up with us so

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far for about fifteen minutes.

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Yeah, thank you so much for having me. I'm like,

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I'm always down to nerd out about data and sasquatch,

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so I'm really excited.

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Well, you've put together some really great, you know pieces

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of you know, visual representation of that data. I know

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you look, you put out some yesterday the day before

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that were really great where folks can go to Instagram

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and check that out. I guess the first question I

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have is why sasquatch? How did you get involved in

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the sasquatch mystery.

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Yeah, I've had like kind of a winding path to

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end up creating the Sasquatch Data Project. But really it

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all started when I was about five. I saw Sasquatch

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legend meete science for the first time, and that's where

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I saw the Patterson Gimblin film, and like, I just

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remember seeing that footage in my brain just kind of exploded.

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I was like, this is the craziest thing I've ever seen,

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and I'm also terrified. So but that kind of like

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that kind of I guess planted the seed for me.

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And I had always been really interested and you know,

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read what I could. And then honestly, when Finding Bigfoot

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came out, I was like in middle school and it

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was the first time I realized that people were really

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like actually devoting their time and energy into researching this subject.

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But at the time I didn't really like realize that

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I could do that in an academic setting or in

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like scientific way. So then NASA became goal and that

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was kind of it until I graduated college, and then

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I just landed at doing this. I just realized, like,

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my passion is researching sasquatch, and you know, I love

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data analysis, I love data science. So this is my take,

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I guess on researching this subject.

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What was really attractive about what you were doing is

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that in twenty twelve we started something up here in

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Pennsylvania called the Keystone Bigfoot Project, and our whole purpose

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was to take all this citing data and put it

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into some sort of like you did, visual representation, and

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so we could go back and look at it historically,

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so see if we could take this data and align

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it to some sort of pattern that we could where

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could we go and best deploy ourselves in the future

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based upon patterns of the past, right, And it was

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quite the mind you menus feet, and none of us

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had the education to do that. I mean, I'm what

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you're doing is rather amazing, and what you've done so

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far is rather amazing. There's a train come through. And

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so that was back in twenty twelve. We started that,

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and we tried to do that. We gave about probably

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about twenty fifteen. We utilized Google Earth as an overlay

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and just kind of, you know, tried to plot it

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that way. But tell us about how you started the

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data project, what was the idea behind it, and how

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did it get going.

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Yeah, so I guess the whole idea got started because

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I had heard. I've always heard folks say like particular

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things that sasquatches do, or you know, different characteristics that

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they say that they have, but then there were never

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numbers or any kind of you know, substance behind the

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statements that people were making. But the thing that really

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made me start this project was I heard someone say

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that sasquatches are more active under a full moon, and

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I was like, well, you know, as far as I know,

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no one's actually run the numbers on that, like taking

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a large amount of data and actually seeing if that's true.

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So I got started by just with that question in mind,

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and I just started going through the FRORO reports by

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hand and making my spreadsheet. And at that time, you know,

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the data set was pretty small. I probably started off

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with about thirty columns and I've grown it to over

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one hundred and eighty now and I've gone through I

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think like twenty six hundred and fifty nine reports so far,

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so I'm pretty pretty deep. But that was the initial

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question that got me interested and was like, Okay, I've

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got to take this idea that I've been sitting on

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and just do it, Like now's the time.

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So what have you found out as an answer to

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that question, so far.

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So far I found out. So something that I like

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to I like to say right off the bat too,

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is when we're taking when we're looking at this data,

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we can make commentary on how reports are basically stated, Like,

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you know, we really can't make statements regarding sasquatch behaviors

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or like their migration habits or anything like that, Like

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we have to look at it from a totally unbiased view.

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So I can't say if they're more active under full

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moon conditions. But I have found that in the data

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that there are more sighting reports in the upper levels

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of the mood illumination, so greater than are equal to

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eighty percent, And that difference, like that increase in citing

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frequency is statistically significant if you're comparing it to the

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middle values. So that's pretty interesting in itself. We also

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see an increase when you are looking at illuminations over

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fifty percent as well. You know why that is, I

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don't know, we can speculate, you know, from both an

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ecological and more humanistic side of things, but it is

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interesting that we do see that, at least so far

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in the data.

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Right now, the only thing and I'm sure, you would

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probably agree with this is the problem with data up

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to the person reporting it to be as accurate as possible,

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and I at times, you know, given the length of

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time we've investigated it, is that what they remember may

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not always be accurate. So one of the things that

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we've tried to do is, you know, go to resources

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when we've gone out and investigated.

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Matt and I.

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Let's say we went out and talked to an investigator

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on Tuesday or a witness on Tuesday, they had a sighting,

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they remember the moon being at one stage, we can

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go and look and say, well, you know, unfortunately you

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might remember it that way. That's just not the case.

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And that's always a problem I had with some of

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this is that folks reporting the data, there's always a

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lot of room for human error.

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Right.

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We could do our due diligence and go and correct that,

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but if it's not caught, you know, it could skew it.

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And I think that's that's a problem with data. But

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I mean, have you gone and done any of that

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checking yourself when you're going through and looking at these reports,

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I mean sometimes you're getting very vague statements of those reports.

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Yeah, I mean I only so when I run any

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kind of data analysis or statistical analysis, I only use

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it when I have complete data, Like I don't. I

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don't really use Class B sightings or class sidings. I'm

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only using Class A sightings really for majority of my analysis.

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And you know, in particular, when we're talking about mud illuminations,

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I'm only using reports that have a complete date so

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that I can go and calculate the muon illumination percentage myself.

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I don't rely on the information in the report. So

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I am very careful with the data that I am using,

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because you know, there is a lot of noise, especially

223
00:13:10.200 --> 00:13:14.200
when you start introducing Class B reports and things like that.

224
00:13:15.559 --> 00:13:18.200
But there's also different corrections and stuff that you can

225
00:13:18.240 --> 00:13:21.320
do when you're running these numbers to make sure that

226
00:13:21.360 --> 00:13:24.600
the signals that you are seeing are you know, not

227
00:13:24.679 --> 00:13:29.639
the result of like a false positive or something with

228
00:13:29.320 --> 00:13:33.120
the statistical testing. So you know, there's ways around it,

229
00:13:33.159 --> 00:13:34.960
and I try to be as careful as you possibly

230
00:13:35.000 --> 00:13:39.080
can and only use like the highest quality reports basically.

231
00:13:40.159 --> 00:13:42.039
But yeah, it really just depends on my question too

232
00:13:42.080 --> 00:13:43.600
of what I'm wanting to know.

233
00:13:44.039 --> 00:13:49.240
I had I had a question, so well, actually it's

234
00:13:49.240 --> 00:13:52.480
a two part question. One is how many reports did

235
00:13:52.519 --> 00:13:56.000
you use and how many reports did you disregard because

236
00:13:56.000 --> 00:13:56.639
they weren't a.

237
00:13:58.240 --> 00:14:04.480
So right now for that particular analysis or just in general.

238
00:14:04.480 --> 00:14:07.080
Okay, you could pick an analysis or in general.

239
00:14:07.120 --> 00:14:09.320
I'm just trying to get to say what the percentage

240
00:14:09.360 --> 00:14:11.519
between an A and a D is, you know what

241
00:14:11.600 --> 00:14:11.840
I mean?

242
00:14:12.000 --> 00:14:13.320
Like that what you've acquired.

243
00:14:13.759 --> 00:14:16.639
So right now on the data set, there are one

244
00:14:16.679 --> 00:14:20.639
hundred and ninety two Class A reports, There's one thousand,

245
00:14:20.720 --> 00:14:25.080
one hundred and eighty three Class B reports, and then

246
00:14:25.080 --> 00:14:29.840
there's eighteen Class C reports, So it's kind of half

247
00:14:29.840 --> 00:14:33.519
and half right now. And then obviously two like those reports, aren't.

248
00:14:35.080 --> 00:14:35.279
You know?

249
00:14:35.360 --> 00:14:39.960
The they don't always have complete data for like everything

250
00:14:39.960 --> 00:14:42.360
that I'm looking for the majority of them don't have

251
00:14:42.440 --> 00:14:47.200
complete data, which is totally fine. But yeah, so that.

252
00:14:46.879 --> 00:14:49.759
Makes sense because you didn't ask the questions to get

253
00:14:50.360 --> 00:14:52.600
not to get the answers you wanted, but to get

254
00:14:52.639 --> 00:14:55.600
the field that you needed to fill in. It's kind

255
00:14:55.600 --> 00:14:58.200
of like if I if me at Forker asked questions

256
00:14:58.200 --> 00:15:00.679
for what we'd like to know, compared you coming in

257
00:15:00.720 --> 00:15:05.240
and asking questions our questions might like Mike might aligne.

258
00:15:05.759 --> 00:15:06.679
But some of your.

259
00:15:06.639 --> 00:15:08.440
Questions you'd be like, oh, man, I wish they would

260
00:15:08.440 --> 00:15:10.440
have asked it. They were from Tulsa, you know what

261
00:15:10.480 --> 00:15:14.039
I mean? Because it was important to what I needed.

262
00:15:13.720 --> 00:15:15.120
To know about Tulsa.

263
00:15:15.279 --> 00:15:15.519
You know.

264
00:15:19.320 --> 00:15:22.080
Yeah, No, Beck, you make a great point there, and

265
00:15:22.120 --> 00:15:24.639
I you know, over the years where we've done this,

266
00:15:24.759 --> 00:15:27.799
there are times Treasure where Baker's given me a public

267
00:15:27.879 --> 00:15:31.399
spanking because I'd asked a question that was uh or

268
00:15:31.440 --> 00:15:34.039
I didn't ask enough questions. Wouldn't you agree, Bake? Was

269
00:15:34.080 --> 00:15:35.919
that was at it? I didn't ask enough. I didn't

270
00:15:35.960 --> 00:15:39.320
go deeper it to go over your.

271
00:15:39.159 --> 00:15:43.879
Information with somebody else. That's why partnerships are good, because

272
00:15:44.120 --> 00:15:46.639
then you can say, okay, hey, I have a eleven

273
00:15:46.720 --> 00:15:51.080
hundred Class A ones, and of them fifty percent or

274
00:15:51.159 --> 00:15:54.960
seventy five percent of them asked an important question to me. Okay,

275
00:15:55.000 --> 00:15:56.759
and then you have a reference and somebody else is

276
00:15:56.799 --> 00:15:59.279
gonna go, yeah, but they asked this question that you

277
00:15:59.360 --> 00:16:02.480
missed that reference back to that and you're like, oh, yeah, Ship,

278
00:16:02.840 --> 00:16:04.039
I can reduce paper.

279
00:16:04.799 --> 00:16:10.120
Yeah, go ahead.

280
00:16:10.120 --> 00:16:13.679
And Matt, So this is actually a follow up to

281
00:16:13.799 --> 00:16:18.440
James's question for you working in the data field, what

282
00:16:18.799 --> 00:16:22.919
is it that you'd like us as researcher says people

283
00:16:22.960 --> 00:16:27.879
doing the interviews, what sort of information is most important

284
00:16:28.639 --> 00:16:29.559
for your data collection?

285
00:16:30.879 --> 00:16:32.679
That's a great question, you know. I was actually just

286
00:16:32.679 --> 00:16:34.440
talking to someone the other day too, who is asking

287
00:16:34.440 --> 00:16:38.600
the same thing, like what what uh fields are useful?

288
00:16:41.039 --> 00:16:42.720
Oh?

289
00:16:42.320 --> 00:16:44.720
Oh no, you lost her?

290
00:16:45.200 --> 00:16:57.000
They got rid of her. Tell them to bring her back. Sorry, hello, sorry,

291
00:16:57.320 --> 00:16:57.879
give me up?

292
00:16:58.399 --> 00:16:58.799
Go ahead.

293
00:17:00.480 --> 00:17:04.119
So yeah, that's a that's a really great question. When

294
00:17:04.200 --> 00:17:07.279
I am looking at witness reports, honestly, the first thing

295
00:17:07.319 --> 00:17:09.559
I look for is a complete date, so like a

296
00:17:09.720 --> 00:17:12.119
specific date that the encounter happened, because we can derive

297
00:17:12.160 --> 00:17:17.319
a lot of information from that, including like extremely comprehensive

298
00:17:17.359 --> 00:17:21.599
weather data. Obviously we can calculate a moon illumination percentage

299
00:17:22.400 --> 00:17:25.640
and other things as well, like we can potentially use

300
00:17:25.680 --> 00:17:29.559
it for like macent modeling or whatever or not maxcent modeling.

301
00:17:29.839 --> 00:17:32.960
That's lat Loan. A lot of too longitude is my

302
00:17:33.000 --> 00:17:35.799
next thing. My brain was thinking ahead. That's the next

303
00:17:35.799 --> 00:17:37.480
thing that I look for is a lot of two longitude

304
00:17:37.519 --> 00:17:39.200
because we can also drive a lot of information from

305
00:17:39.240 --> 00:17:44.599
that too. But when it comes to like physical descriptions,

306
00:17:44.720 --> 00:17:47.799
that's something that I'm particularly interested in, especially when we're

307
00:17:47.799 --> 00:17:52.160
looking at things on a regional scale. I'm really interested

308
00:17:52.240 --> 00:17:56.759
in like the hair condition, where they maddie or matted

309
00:17:56.960 --> 00:18:01.400
like shaggy nasty, or were they like pretty clean, because

310
00:18:01.839 --> 00:18:05.720
potentially it could tell us about their social dynamics. We

311
00:18:05.759 --> 00:18:08.839
see this and the other great apes things that I

312
00:18:08.880 --> 00:18:13.359
look for are like progmatism, like does their job protrude

313
00:18:13.400 --> 00:18:15.119
from their face or do they have you know, was

314
00:18:15.119 --> 00:18:19.440
it a flat face? You know. I have like a

315
00:18:19.480 --> 00:18:22.119
worksheet I would be happy to send you to that

316
00:18:22.279 --> 00:18:26.279
has basically every column in my data set like spelled

317
00:18:26.279 --> 00:18:29.519
out for it, specifically for people who are doing like

318
00:18:29.640 --> 00:18:32.839
witness follow up interviews that kind of give you an

319
00:18:32.839 --> 00:18:34.559
idea of some things to ask.

320
00:18:35.400 --> 00:18:37.440
We would we would definitely appreciate that.

321
00:18:38.039 --> 00:18:39.359
Oh yeah, yeah.

322
00:18:39.160 --> 00:18:42.799
Yeah, I can definitely send that over. But like I said,

323
00:18:42.799 --> 00:18:45.799
I have like one hundred and eighty columns that I'm

324
00:18:45.799 --> 00:18:48.519
trying to fill out in the spreadsheet for every single report,

325
00:18:48.599 --> 00:18:53.279
So anything related to you know, the environmental, behavioral or

326
00:18:53.359 --> 00:18:57.160
physical traits of sasquatches, like I'm interested in the goal

327
00:18:57.279 --> 00:18:59.680
is to have a column for kind of everything. If

328
00:18:59.720 --> 00:19:02.759
you can ask a question about the report, Like, I

329
00:19:02.799 --> 00:19:06.000
want to have information easily accessible that you can go

330
00:19:06.039 --> 00:19:09.680
and grab from the data set. But yeah, really, really,

331
00:19:09.759 --> 00:19:13.319
the things that are missing that I wish I had

332
00:19:13.480 --> 00:19:15.799
more of is definitely the lat Moan data and then

333
00:19:15.880 --> 00:19:17.640
like a complete date of the encounter, but I know

334
00:19:17.680 --> 00:19:21.680
that's not always possible to get.

335
00:19:25.960 --> 00:19:26.839
Henry, You're up next.

336
00:19:26.839 --> 00:19:30.640
You had a question, Yes, I wanted to ask what

337
00:19:30.799 --> 00:19:33.279
sort of patterns do you look for? Do you look

338
00:19:33.319 --> 00:19:36.319
for patterns in the reports that you've collected?

339
00:19:37.559 --> 00:19:42.079
Yeah, So when it comes to the patterns, I always

340
00:19:42.119 --> 00:19:45.640
have a pre defined question of what I'm asking. I'm

341
00:19:45.680 --> 00:19:51.039
not necessarily looking to answer my questions a certain way.

342
00:19:51.119 --> 00:19:53.880
I just I'll think of something. So like one of

343
00:19:53.920 --> 00:19:57.519
my one of my favorite things that I've looked into

344
00:19:57.960 --> 00:20:02.400
is this relationship between a witness's fear level during the

345
00:20:02.519 --> 00:20:06.319
encounter and the associated estimated height of the sasquatch. So

346
00:20:06.960 --> 00:20:10.039
that was my question because I hear quite often, like

347
00:20:10.079 --> 00:20:12.920
you know, people who are more freaked out, they might

348
00:20:12.960 --> 00:20:15.599
think it's bigger than it actually is, and this is

349
00:20:15.640 --> 00:20:20.160
a very well documented documented psychological phenomenon. So I was like, well,

350
00:20:20.200 --> 00:20:24.359
you know, we could potentially see that in witness reports.

351
00:20:24.599 --> 00:20:28.200
So that's my question. My question is how does or

352
00:20:28.319 --> 00:20:31.960
does the estimated heights of the sasquatch change if you

353
00:20:32.160 --> 00:20:36.359
introduce witness fear levels into things and it turns out

354
00:20:36.359 --> 00:20:40.960
it does. So like I love looking at things like

355
00:20:41.000 --> 00:20:43.400
that that are kind of it doesn't really matter if

356
00:20:43.400 --> 00:20:45.799
the witness is accurate or not in the height estimate,

357
00:20:46.000 --> 00:20:49.000
like in that case, it doesn't only matter if you know,

358
00:20:49.079 --> 00:20:51.519
they said it was eight feet but it was actually

359
00:20:51.519 --> 00:20:53.640
only six and a half feet tall or something. It's

360
00:20:53.680 --> 00:20:57.480
more about just the general change in the data, if

361
00:20:57.480 --> 00:21:00.759
that makes sense. So I love looking for patterns like

362
00:21:00.839 --> 00:21:05.359
that where it would be extremely difficult to hoax, especially

363
00:21:05.400 --> 00:21:12.759
over decades and a large geographic span. And I love

364
00:21:12.839 --> 00:21:14.799
looking at I don't know, just kind of like a

365
00:21:14.839 --> 00:21:19.680
backdoor way into investigating witness reports that might not be

366
00:21:20.519 --> 00:21:24.480
you know, I have a forefront of people's minds.

367
00:21:25.640 --> 00:21:29.920
Interesting. Oh that's very interesting. I like the purpose behind that.

368
00:21:30.559 --> 00:21:33.119
Terrorized by a four foot tall sasquatch. You know, it

369
00:21:33.240 --> 00:21:37.079
was horrifying. Scare the crap out of me. Hey they're

370
00:21:37.119 --> 00:21:39.839
out there, folks. They start out as baby somewhere right

371
00:21:40.039 --> 00:21:41.920
or the Alba twitch. You got to get a lot

372
00:21:41.920 --> 00:21:45.079
of Alba twitches. Would you have a question in the

373
00:21:45.160 --> 00:21:48.559
chat from Scott Dieter. Lee are a good friend Scott,

374
00:21:48.599 --> 00:21:50.400
and it was to the entire group, but we'll let

375
00:21:50.599 --> 00:21:53.519
Trash will go first. Do you think that the community

376
00:21:53.559 --> 00:21:57.440
could standardize some sort of interview data gathering protocol?

377
00:21:58.559 --> 00:22:03.480
I think it would be extremely been official because purely

378
00:22:03.599 --> 00:22:09.599
from like a scientific standpoint, having standardization is essential to

379
00:22:09.759 --> 00:22:15.559
any kind of investigation, like making sure you know everyone's asking.

380
00:22:16.559 --> 00:22:19.440
In an ideal world, everyone would ask the same exact

381
00:22:19.519 --> 00:22:22.000
questions in the same exact way, in the same order.

382
00:22:23.200 --> 00:22:28.119
I recognize though that that's not possible really, but we

383
00:22:28.160 --> 00:22:33.000
would definitely definitely benefit from something like that so that

384
00:22:33.079 --> 00:22:35.519
we could make sure that we're extracting as much information

385
00:22:35.599 --> 00:22:39.279
as we possibly can from the witness interviews.

386
00:22:40.680 --> 00:22:44.359
Yeah, hmm, right.

387
00:22:45.400 --> 00:22:47.440
I think you have to leave the opportunity for them.

388
00:22:47.720 --> 00:22:51.039
You know, the human aspect of it too. There's you

389
00:22:51.079 --> 00:22:53.839
don't want it to be an interrogation. You want it

390
00:22:53.880 --> 00:22:57.000
to be an interview, right, And sometimes as you're asking

391
00:22:57.599 --> 00:22:59.720
a hell of a lot of questions, that seems more,

392
00:23:00.359 --> 00:23:03.440
you know, of an interrogation then it does an interview.

393
00:23:03.559 --> 00:23:06.359
But if you can answer a lot of the same question.

394
00:23:06.400 --> 00:23:07.839
You know, a lot of the same You can answer

395
00:23:07.839 --> 00:23:10.720
a lot of the questions with a question. It makes

396
00:23:10.759 --> 00:23:13.160
a difference. I think one of the things that it helps, though,

397
00:23:13.319 --> 00:23:16.599
is eliminate leading questions and takes that bias out of

398
00:23:16.640 --> 00:23:21.680
the investigator and puts, like you said, a standard operating

399
00:23:22.799 --> 00:23:25.440
you know, form or data set that you can ask

400
00:23:25.519 --> 00:23:28.680
questions that aren't going to be leading, and you take

401
00:23:28.720 --> 00:23:29.200
a lot.

402
00:23:29.039 --> 00:23:29.359
Of that.

403
00:23:31.240 --> 00:23:33.000
I don't want to say guests work. If you take

404
00:23:33.039 --> 00:23:35.160
a lot of that bias out of the equation then

405
00:23:35.880 --> 00:23:42.319
and I think that's really important. Researchers still understand the

406
00:23:42.440 --> 00:23:49.039
power they have in forcing questions out of witnesses or

407
00:23:49.079 --> 00:23:53.039
forcing answers out of witnesses unintentionally, that you're goading them

408
00:23:53.079 --> 00:23:57.279
along and you're you're setting them up. You're not really

409
00:23:57.319 --> 00:24:01.680
helping them give you a true recollection of what they encountered.

410
00:24:04.279 --> 00:24:09.880
It's problematic. I guess my question would be everybody still alive?

411
00:24:10.400 --> 00:24:14.200
Yeah, we're still alive. I guess my question would be,

412
00:24:15.680 --> 00:24:20.279
thanks man, some of one to ten? Where do you

413
00:24:20.440 --> 00:24:24.960
believe this entity actually exists?

414
00:24:27.599 --> 00:24:27.680
Like?

415
00:24:28.920 --> 00:24:29.200
Where?

416
00:24:29.440 --> 00:24:29.680
Wait?

417
00:24:29.799 --> 00:24:32.160
Can you say that again? Did you say where they exist?

418
00:24:33.160 --> 00:24:33.440
Well?

419
00:24:33.640 --> 00:24:37.240
No, let me. Let me rephrase that on a scale

420
00:24:37.319 --> 00:24:42.599
of one to ten, ten being the greatest, do you

421
00:24:42.720 --> 00:24:46.359
believe that this entity actually exists?

422
00:24:46.720 --> 00:24:50.480
Oh, actually exists? Sorry, I would say I'm at like

423
00:24:52.119 --> 00:24:57.759
a nine point nine at this point. Awesome, Like yeah,

424
00:24:57.759 --> 00:25:00.440
and doing the data project too is just kind of

425
00:25:00.480 --> 00:25:03.240
pushed me further up the scale as well. Like the

426
00:25:03.240 --> 00:25:07.160
more that I see, the more non random patterns that

427
00:25:07.240 --> 00:25:10.720
I see, the more I'm convinced, especially when you start

428
00:25:10.759 --> 00:25:16.960
recognizing too that some of these patterns mirror known you know,

429
00:25:17.079 --> 00:25:21.559
nocturnal predator behaviors, or they mirror like known great behavior

430
00:25:21.799 --> 00:25:28.599
or you know, anything like that. So yeah, definitely obviously

431
00:25:28.680 --> 00:25:32.559
like seeing one would push me over into a tend.

432
00:25:32.640 --> 00:25:35.160
But the more I look at the data, the more

433
00:25:35.200 --> 00:25:40.799
that I just keep asking questions and keep digging, and

434
00:25:40.920 --> 00:25:41.799
the more I learn it.

435
00:25:41.920 --> 00:25:47.079
Just I'm just I'm right there, you know, because I

436
00:25:47.119 --> 00:25:49.400
am a lot of people that ask me. They know

437
00:25:49.519 --> 00:25:52.759
that I'm into this field, and they ask me that

438
00:25:52.880 --> 00:25:57.839
same question, and I say, yeah, I definitely believe that

439
00:25:57.880 --> 00:26:02.440
there is this entity that does exist, but I'm not

440
00:26:02.519 --> 00:26:06.799
one hundred percent, So I'm kind of running right alongside

441
00:26:06.799 --> 00:26:13.480
of you with that same analytical belief that, Yeah, I'm

442
00:26:13.480 --> 00:26:17.039
not one hundred percent, but boy, I'm kind of close

443
00:26:17.119 --> 00:26:17.480
to it.

444
00:26:18.880 --> 00:26:21.400
Well, And I think I'm going to piggyback off you

445
00:26:21.480 --> 00:26:24.359
there for a for a minute advance and go into

446
00:26:24.400 --> 00:26:28.559
another question in terrestrial is you're nine point nine, you know,

447
00:26:28.640 --> 00:26:31.279
a nine point nine on that scale of one to ten,

448
00:26:32.039 --> 00:26:33.880
and you're pretty you know, you did work with NASA.

449
00:26:33.920 --> 00:26:36.920
To me, that's that's pretty scientific. It doesn't get much

450
00:26:36.960 --> 00:26:41.240
more scientific than that. Why do you think science has

451
00:26:41.279 --> 00:26:44.079
a soul has a problem with Bigfoot?

452
00:26:46.359 --> 00:26:51.160
You know, that's a really good question. I think it's

453
00:26:51.240 --> 00:26:55.839
partly due to the stigma. I mean, obviously there's a

454
00:26:55.839 --> 00:27:00.200
stigma around it, and there's it's kind of wild because

455
00:27:00.200 --> 00:27:02.680
there's even a stigma around just bringing it up as

456
00:27:02.720 --> 00:27:08.960
a question, like within academia. It's definitely people instantly kind

457
00:27:09.039 --> 00:27:12.680
of write you off. For the most part, I think

458
00:27:12.720 --> 00:27:15.400
it's just how it's been handled through the decades.

459
00:27:16.119 --> 00:27:16.319
You know.

460
00:27:16.400 --> 00:27:18.400
Personally, I think part of it is due to how

461
00:27:18.440 --> 00:27:22.240
the media handled it and how it kind of how

462
00:27:22.319 --> 00:27:25.960
they kind of shaped society to see the subject as

463
00:27:25.960 --> 00:27:28.720
a whole or to see, yeah, to see the subject

464
00:27:28.759 --> 00:27:32.440
as a whole throughout the decades and whatnot. But I

465
00:27:32.519 --> 00:27:34.480
just think that too. There's a lot of funding on

466
00:27:34.559 --> 00:27:37.599
the line, so people are scared to get their funding

467
00:27:37.640 --> 00:27:41.880
taken away. There. You know, your reputation is very important

468
00:27:42.079 --> 00:27:44.799
in academia and the projects that your on are very important.

469
00:27:44.880 --> 00:27:47.160
So you want people to continue to want to work

470
00:27:47.160 --> 00:27:51.000
with you, and you need again funding. That's a big

471
00:27:51.039 --> 00:27:55.519
part of things. Yeah, I think you know. Obviously I

472
00:27:55.519 --> 00:28:00.720
don't know for sure, but just from my initial thoughts,

473
00:28:01.200 --> 00:28:04.000
I'm assuming that has a lot to do with it.

474
00:28:05.839 --> 00:28:08.759
That's a good answer. We'll give you points for that one.

475
00:28:08.400 --> 00:28:11.640
Well, go ahead, I mean you do see that, And

476
00:28:11.880 --> 00:28:16.799
like I'll use Ghostbusters as a common movie that everybody knows.

477
00:28:16.839 --> 00:28:17.759
But the fact was.

478
00:28:17.759 --> 00:28:21.480
Is they got thrown out of college because they were

479
00:28:22.039 --> 00:28:25.079
because people in the area noticed what they were doing.

480
00:28:25.799 --> 00:28:28.160
To a degree, the library incident kind of pushed it

481
00:28:28.200 --> 00:28:30.559
over the edge. But there's other movies.

482
00:28:30.279 --> 00:28:34.759
Where when someone starts to do paranormal investigation or something

483
00:28:34.799 --> 00:28:38.079
like that, Rose Red's and other movie Stephen King. I

484
00:28:38.079 --> 00:28:40.240
know they're written novel and whatever, but it shows how

485
00:28:40.799 --> 00:28:44.119
them believing in something that the rest of the tenured

486
00:28:44.160 --> 00:28:47.359
academia say, oh no, you can't do that they either

487
00:28:47.400 --> 00:28:50.160
shut up or they think. Yeah, So it is important

488
00:28:50.160 --> 00:28:52.839
to walk the line. And I'm glad that you're able

489
00:28:52.880 --> 00:28:55.000
to do that because that way because the key thing

490
00:28:55.119 --> 00:28:58.559
is is in any of this is research doesn't pay cash.

491
00:28:58.799 --> 00:29:00.640
You need to have a job, you know.

492
00:29:02.240 --> 00:29:04.839
Yeah, we'd love to be doing this full time, but

493
00:29:04.920 --> 00:29:09.160
that doesn't exist yet. All right, before we jump into

494
00:29:09.160 --> 00:29:11.759
more questions, we're gonna take our break here, folks. You're

495
00:29:11.799 --> 00:29:14.799
listening to the Sasquatch Experience. Sean Forker, Matt Arnoer, James

496
00:29:14.880 --> 00:29:17.799
Baker Vance and has been our guest Tonight Terrestrial. We'll

497
00:29:17.799 --> 00:29:21.319
be back right after this stay tuned fun show we're

498
00:29:21.319 --> 00:29:23.640
having the night here. We'll be right back with Vance

499
00:29:23.759 --> 00:29:24.920
and the Big Football Worn.

500
00:29:25.799 --> 00:29:28.559
News team assemboy.

501
00:29:34.759 --> 00:29:37.039
I think that's why you have so many bigfoot sightings here.

502
00:29:39.119 --> 00:29:44.519
Good wee people. I think I see bigfoot dude.

503
00:29:44.519 --> 00:29:47.079
That's a mailbox Because we're downtown. You don't come here.

504
00:29:48.720 --> 00:29:48.960
Ah.

505
00:29:49.079 --> 00:29:52.839
Yes, anybody have a big foot costume that can put

506
00:29:52.880 --> 00:29:56.039
over a mailbox, I'll give you five bucks. How about

507
00:29:56.079 --> 00:30:00.880
that We'll show them. Well. Happy even to you all.

508
00:30:01.160 --> 00:30:05.039
I hope you're all surviving the summer swelter and storms.

509
00:30:05.640 --> 00:30:08.000
We certainly had our sheriff storms last night. I think

510
00:30:08.000 --> 00:30:11.119
I'm the only one that still has power on lucky me.

511
00:30:12.359 --> 00:30:15.680
You know, the last time we talked, I mentioned to

512
00:30:15.720 --> 00:30:18.079
you I was doing some research and didn't find any

513
00:30:18.119 --> 00:30:22.839
bigfoot reports for the month of July of this year. Well,

514
00:30:22.880 --> 00:30:26.920
that seems to have changed. And here is a quoted

515
00:30:27.039 --> 00:30:33.039
report to the BFRO by a witness who stated the following.

516
00:30:34.240 --> 00:30:37.519
I was on vacation and just got back yesterday, July

517
00:30:37.720 --> 00:30:43.160
twenty third of twenty twenty five. When this happened. We

518
00:30:43.200 --> 00:30:47.160
rented a cabin outside of Gallenburg, Tennessee. In the hot

519
00:30:47.160 --> 00:30:52.440
tub outside, the woods were silent, then we heard some

520
00:30:52.720 --> 00:30:58.920
tree movement. Me, my wife, and my wife's girlfriend were there. Yes.

521
00:30:59.720 --> 00:31:02.480
Is it wrong for a man and his wife and

522
00:31:02.960 --> 00:31:08.599
girlfriend do share a hot tub? I think not. I

523
00:31:08.720 --> 00:31:11.319
was just looking around the woods and saw what looked

524
00:31:11.359 --> 00:31:15.240
like a black gorilla's head and shoulder stinking out of

525
00:31:15.279 --> 00:31:18.839
the brush about one hundred yards away. The sun was

526
00:31:18.880 --> 00:31:22.079
shining directly on that section of the brush, but it

527
00:31:22.240 --> 00:31:26.319
still looked completely black. I couldn't make out any other

528
00:31:26.400 --> 00:31:30.599
features other than an outline. It did seem like a

529
00:31:30.640 --> 00:31:34.960
fur texture around the edges with a round head. The

530
00:31:35.000 --> 00:31:39.519
blackness of it is what I noticed initially. I stared

531
00:31:39.519 --> 00:31:41.960
at it for a few minutes and thought it looked

532
00:31:42.000 --> 00:31:45.279
like a bigfoot. But I figured I was psyching myself out,

533
00:31:45.440 --> 00:31:49.279
so I intentionally looked away for about a minute, just

534
00:31:49.319 --> 00:31:53.359
staring at the cabin wall. When I looked back, it

535
00:31:53.480 --> 00:31:58.079
was gone. Another minute or two later, we heard trees crackling.

536
00:31:58.880 --> 00:32:01.680
I looked around for about another ten minutes and didn't

537
00:32:01.720 --> 00:32:06.440
see anything else, no other experiences. Why we were there.

538
00:32:07.519 --> 00:32:09.799
Maybe it was a mailbox in the bush that fell over.

539
00:32:10.839 --> 00:32:15.880
Who knows when we come back. Yes, we're gonna promote

540
00:32:15.880 --> 00:32:19.759
it for the last time. Let's go camping.

541
00:32:22.880 --> 00:32:26.519
You're listening to the big footballhorn right here on the Sasquatch.

542
00:32:26.000 --> 00:32:41.400
Experience as anybody ever told you. Hey, nice knockers. If not,

543
00:32:41.920 --> 00:32:46.359
just visit got knockers dot org read about the encounter

544
00:32:46.480 --> 00:32:50.720
that kicked this whole thing off. Plus you comparchase one, two,

545
00:32:50.880 --> 00:32:54.599
three or more Tree Knockers. I'm not sure what you

546
00:32:54.720 --> 00:32:58.400
thought we were talking about. Got Knockers has a plethora

547
00:32:58.480 --> 00:33:02.599
of gifts and merchandise too, from awesome apparel, ware, and

548
00:33:02.880 --> 00:33:07.880
even something for the baby. Find jewelry and sausage to

549
00:33:07.960 --> 00:33:11.519
please anyone's taste. Bud stop on buy and give a

550
00:33:11.519 --> 00:33:15.200
hello to Gwendolyn and Michael Perse. Now that you know

551
00:33:15.240 --> 00:33:18.799
where to gets some great knockers. They make fun gifts

552
00:33:18.920 --> 00:33:24.039
or accessories for the squatch bag. Just visit Godknockers dot

553
00:33:24.160 --> 00:33:49.000
org again got knockers dot org. Well, folks were only

554
00:33:49.200 --> 00:33:53.440
four and a half days away from the PA Bigfoot

555
00:33:53.559 --> 00:33:58.559
camping Adventure. It's this Friday and Saturday, August twenty second

556
00:33:58.720 --> 00:34:07.640
and twenty at the Benners Metal Run RV Campground in Farmington, Pennsylvania.

557
00:34:08.400 --> 00:34:12.239
An exciting lineup of speakers out of the sixteen, here's

558
00:34:12.400 --> 00:34:18.239
just naming a few. Ron Moorhead, Sean Forker, Lyle Blackburn,

559
00:34:18.840 --> 00:34:24.559
Stan Gordon Matt Arner, and of course doctor Jeff Meldrum.

560
00:34:25.000 --> 00:34:28.280
They'll be workshops so you can dive into Bigfoot sightings,

561
00:34:28.400 --> 00:34:32.599
evidence and analysis and the science behind the legend. They'll

562
00:34:32.639 --> 00:34:36.440
also be night hikes join a guided search deep into

563
00:34:36.480 --> 00:34:39.880
the woods. Who knows what you might find. They'll be

564
00:34:39.960 --> 00:34:44.119
live music in movies to enjoy entertainment all weekend long.

565
00:34:44.239 --> 00:34:47.800
Plus they'll be vendors and food trucks so that you

566
00:34:47.880 --> 00:34:52.960
can grab some delicious food and shop for unique Bigfoot gear.

567
00:34:54.159 --> 00:35:01.039
Just go to PA Bigfoot Campingadventure dot com. Again PA

568
00:35:01.400 --> 00:35:07.400
Bigfoot Camping Adventure dot Com, thanks again for listening to

569
00:35:07.440 --> 00:35:10.840
this edition of the big Footbullhorn right here on Anomalous

570
00:35:11.000 --> 00:35:17.920
Entertainment's Sasquatch Experience. And of course, as always, until we

571
00:35:18.039 --> 00:35:20.199
meet again, keep your toe in the mind.

572
00:35:20.280 --> 00:35:35.760
Mind Now, that was really good dvance, well done, well done.

573
00:35:35.840 --> 00:35:41.480
My friend father, yes, and you know he comes with

574
00:35:41.480 --> 00:35:43.119
a mute button, folks, but he doesn't know how to

575
00:35:43.159 --> 00:35:45.000
use it. The bull in the China Shop, James Baker.

576
00:35:45.039 --> 00:35:49.760
Everybody back in the chair, lacking WD forty. But before

577
00:35:49.760 --> 00:35:51.079
we went to the break, we were asking us some

578
00:35:51.079 --> 00:35:54.079
really good questions of our guest Tonight Terrestrial. If you're

579
00:35:54.119 --> 00:35:56.679
just joining us at the midpoint of the show, for

580
00:35:56.760 --> 00:35:59.440
the love of god, hit your mute button, Baker, and uh,

581
00:36:00.199 --> 00:36:03.960
we have I asked for one hour a week. That's

582
00:36:04.360 --> 00:36:08.440
one hour a week. Anyhow, we have trestoral on the

583
00:36:08.440 --> 00:36:10.920
show from the Sasquatch Data Project. We had a great

584
00:36:11.280 --> 00:36:13.440
you know discussion at the beginning, and we're going to

585
00:36:13.480 --> 00:36:17.199
carry on with that. Henry has looks like he left

586
00:36:17.440 --> 00:36:21.360
or hopefully he's okay, Matt Baker, vance any questions before

587
00:36:21.400 --> 00:36:24.320
I move on to the next segment. Yeah, you know what,

588
00:36:25.679 --> 00:36:31.840
Oh go ahead, No, I'm going into that question. You do, Okay.

589
00:36:32.440 --> 00:36:36.079
So, from what I understand, Thrustol is you're taking data

590
00:36:36.159 --> 00:36:40.079
from the the BFRO sidings. Correct, they're the Class a's.

591
00:36:40.639 --> 00:36:47.119
Have you looked in perhaps started looking at possibly in

592
00:36:47.199 --> 00:36:52.559
putting the information from historical reports like uh, those that

593
00:36:52.760 --> 00:36:57.239
John Green had had written in his book, or even

594
00:36:57.280 --> 00:37:00.840
going back further with some of the some of the

595
00:37:02.159 --> 00:37:05.159
reports before even you know, Bigfoot was in me.

596
00:37:06.159 --> 00:37:09.800
Yeah, so I actually I actually just got access to

597
00:37:09.920 --> 00:37:13.199
John Green's data SEID the other day. So I'm starting

598
00:37:13.239 --> 00:37:16.280
to look through that and see what I can do

599
00:37:16.320 --> 00:37:18.719
with it and see how I can incorporate it into

600
00:37:18.760 --> 00:37:22.119
the data set that I'm making. The eventual goal of

601
00:37:22.159 --> 00:37:26.480
this is to basically have a massive catalog of reports.

602
00:37:26.599 --> 00:37:30.559
So the bf O is just step one, and you know,

603
00:37:30.719 --> 00:37:33.320
it is just me working on this, so it takes

604
00:37:33.400 --> 00:37:37.599
a while. You know, I'm not manually I'm manually reviewing reports,

605
00:37:37.639 --> 00:37:42.079
but I don't manually input them anymore. I'm using AI

606
00:37:42.119 --> 00:37:45.000
to help me do that. Essentially created this like whole

607
00:37:45.000 --> 00:37:49.320
pipeline that does it for me. But yeah, the the

608
00:37:49.320 --> 00:37:53.480
the eventual goal is to incorporate pretty much as as

609
00:37:53.480 --> 00:37:57.360
many reports as possible, historical, you know, all the way

610
00:37:57.440 --> 00:38:02.000
up to present day. So yeah, I'm starting to go

611
00:38:02.079 --> 00:38:05.519
through John Green's data set and see what that's all about,

612
00:38:05.559 --> 00:38:08.480
which I'm really excited about. And I do have a

613
00:38:08.519 --> 00:38:12.000
few reports from like the North America Wedding Conservancy as

614
00:38:12.039 --> 00:38:15.920
well in the data set. But yes, yeah, let's see

615
00:38:16.000 --> 00:38:16.760
eventual goal.

616
00:38:17.719 --> 00:38:25.159
Awesome, awesome, Yeah Baker or Vance? What at a time?

617
00:38:27.760 --> 00:38:30.480
Van Vance is dead? Where did he go?

618
00:38:33.039 --> 00:38:37.000
Okay, sorry I was a little late to the chair

619
00:38:37.719 --> 00:38:41.760
at some extra problems to deal with. Anyway, First I

620
00:38:41.800 --> 00:38:44.440
want to thank you for answering our questions. And secondly

621
00:38:44.480 --> 00:38:46.599
it is I want to think thank you for trying

622
00:38:46.599 --> 00:38:48.679
to put this data out there, because I think a

623
00:38:48.719 --> 00:38:52.320
lot of times we get do you.

624
00:38:51.960 --> 00:38:54.880
Do you have trouble producing your data?

625
00:38:55.719 --> 00:38:58.039
I'm gonna put it this way, getting your data out

626
00:38:58.119 --> 00:39:01.440
because of the latest fake site and the latest problems

627
00:39:01.480 --> 00:39:03.599
we've had that most news that comes out of the

628
00:39:03.599 --> 00:39:07.800
Bigfoot community as fifty percent is bunkable, if we'll call that.

629
00:39:08.880 --> 00:39:15.440
Yeah, no, I you know, I know just because I'm using, uh,

630
00:39:15.679 --> 00:39:20.079
what the BFO has available. I honestly, I gotta admit,

631
00:39:20.159 --> 00:39:23.159
I don't really keep up with what's you know, the

632
00:39:23.280 --> 00:39:28.320
latest sighting or video is because you know, the majority

633
00:39:28.400 --> 00:39:31.280
of it is just, at least on the video standpoint,

634
00:39:31.280 --> 00:39:33.239
the majority of it it just hoaxes.

635
00:39:34.679 --> 00:39:36.960
And so I do that's the best answer, because that's

636
00:39:37.000 --> 00:39:39.079
how I feel. I don't look at any of it.

637
00:39:39.519 --> 00:39:42.280
Yeah, I honestly don't really keep up with it. My

638
00:39:42.480 --> 00:39:47.239
brain is purely on getting through these reports and looking

639
00:39:47.280 --> 00:39:50.599
through the data set, so I don't really let it

640
00:39:50.679 --> 00:39:54.960
influence what I'm doing, honestly, and for me getting this

641
00:39:55.079 --> 00:39:57.599
information out there is I'm just I'm just trying to

642
00:39:57.719 --> 00:40:01.559
present the numbers and then you know, kind of go

643
00:40:01.679 --> 00:40:05.639
from there. I really try to not take any kind

644
00:40:05.679 --> 00:40:09.199
of strong stance on anything. I try to remain very

645
00:40:09.239 --> 00:40:13.280
neutral as unbiased as possible and just kind of say, well,

646
00:40:13.360 --> 00:40:15.719
this is what the data is saying, and you know,

647
00:40:16.039 --> 00:40:18.159
you could take this this way or this way, or

648
00:40:18.199 --> 00:40:20.800
it's something else that we don't know about, but it's

649
00:40:20.840 --> 00:40:24.079
interesting that this is the pattern that we're seeing. Basically,

650
00:40:25.559 --> 00:40:27.480
so I kind of I try to let the numbers

651
00:40:27.480 --> 00:40:31.559
speak for themselves, and you know, people are free to

652
00:40:31.639 --> 00:40:35.559
interpret the results as they will, but I just think

653
00:40:35.559 --> 00:40:37.760
it's really important to do that. I think it's really

654
00:40:37.760 --> 00:40:42.480
important to not really a strong stance. So yeah, I

655
00:40:42.519 --> 00:40:43.599
hope I answered your question.

656
00:40:43.880 --> 00:40:47.440
No, no, you you you answered. You actually answered a

657
00:40:47.440 --> 00:40:50.119
better question than I asked. Because the fact is.

658
00:40:50.320 --> 00:40:53.119
That that I think that your your stance on it.

659
00:40:53.159 --> 00:40:55.239
And the nice thing is is when somebody confronts you

660
00:40:55.280 --> 00:40:57.360
and says, hey, you're just flulllah blah blah blah, You'll

661
00:40:57.400 --> 00:40:59.920
be like, see this big pack of papers, this is

662
00:41:00.119 --> 00:41:03.199
what I started with, this is what I've got and

663
00:41:03.280 --> 00:41:05.599
since you didn't read either one of these, you can

664
00:41:05.679 --> 00:41:06.760
go away.

665
00:41:07.119 --> 00:41:09.199
That's the positive way to say it.

666
00:41:09.199 --> 00:41:12.440
I would have maybe added a little extra Urban Dictionary, but.

667
00:41:12.440 --> 00:41:18.159
Yeah, yeah, you put a lot of truth in there, Baker.

668
00:41:18.360 --> 00:41:21.960
You know, with what you're presenting terrestrial, right, it's unemotional,

669
00:41:22.639 --> 00:41:27.119
it's it's fact from the information you have, right, and

670
00:41:27.400 --> 00:41:29.280
and people have a hard time with that. I'm even

671
00:41:29.360 --> 00:41:31.480
listen going through and looking at some of the comments

672
00:41:31.679 --> 00:41:34.159
you know in the chat room right now, like you know,

673
00:41:34.239 --> 00:41:37.599
someone miffed off about you know, plenty of real video

674
00:41:37.760 --> 00:41:40.960
for your information. Oh, there's not. I have yet to

675
00:41:41.000 --> 00:41:43.800
see something that's compelling enough to say, oh hot, damn,

676
00:41:43.880 --> 00:41:46.840
that's a big foot. Just doesn't It hasn't happened yet.

677
00:41:47.360 --> 00:41:49.599
But squads of videos are pretty good though.

678
00:41:49.719 --> 00:41:51.280
Yeah, well, you know, we have a lot of fun

679
00:41:51.320 --> 00:41:54.599
with those AI videos as well. But the reality is

680
00:41:54.679 --> 00:41:58.960
all that stuff's clogging up the pipe. It's the pipe.

681
00:41:59.159 --> 00:42:00.840
And when you can look at it and break it

682
00:42:00.920 --> 00:42:03.480
down and you're just looking at raw data, you know,

683
00:42:03.559 --> 00:42:06.800
this is what it shows. That's a that's a great

684
00:42:06.800 --> 00:42:10.920
starting point or a great just factual point, like you

685
00:42:11.039 --> 00:42:14.800
might feel that way, but this data is a bias,

686
00:42:14.920 --> 00:42:17.760
you know, this is this is telling a different story

687
00:42:17.480 --> 00:42:20.400
than in how you feel, and it's important we get

688
00:42:20.440 --> 00:42:22.599
into that mindset. We're going to keep doing the same

689
00:42:22.679 --> 00:42:24.679
thing that we've been doing for the last sixty years,

690
00:42:24.920 --> 00:42:30.519
which is chasing our perpetual tales and not speaking for

691
00:42:30.559 --> 00:42:34.000
everybody else here. You know, I've had an experience with

692
00:42:34.079 --> 00:42:38.360
something I can't explain that it was really impactful to me.

693
00:42:38.559 --> 00:42:41.639
It was very I don't want to say life changing

694
00:42:41.679 --> 00:42:42.840
because that's super.

695
00:42:43.960 --> 00:42:44.519
You know, like.

696
00:42:46.039 --> 00:42:51.679
Dramatic, but it it changed my thought process onto the

697
00:42:51.760 --> 00:42:54.519
subject that brought it into reality for me, but I'm

698
00:42:54.559 --> 00:42:57.880
still very skeptical. I think having an experience of my

699
00:42:57.920 --> 00:43:01.199
own made it worse and van you know it was,

700
00:43:01.400 --> 00:43:04.760
you know really, And I'm bringing back advance back on

701
00:43:04.880 --> 00:43:08.159
vance oaticiting with something he couldn't explain years ago. And

702
00:43:08.239 --> 00:43:11.679
I think that when you have an encounter or you

703
00:43:11.719 --> 00:43:14.079
have an experience with something and there's no definitive to

704
00:43:14.119 --> 00:43:17.760
what you've seen. To me, that's made me a little

705
00:43:17.800 --> 00:43:20.960
bit more hostile to these folks that are adamant, like

706
00:43:21.880 --> 00:43:24.679
I what gives you the right to say that we

707
00:43:24.719 --> 00:43:29.119
don't have anything to base this off of, Like, as

708
00:43:29.239 --> 00:43:33.199
much as we want to say this is real, there's

709
00:43:33.239 --> 00:43:41.519
still no proof positive that it is. Yeah, at least

710
00:43:41.559 --> 00:43:45.119
with the data and the tremendous amounts of it. It

711
00:43:45.159 --> 00:43:48.639
gives us something to lean on and say, well, we

712
00:43:48.719 --> 00:43:51.840
might not have a body, but we do have this,

713
00:43:52.480 --> 00:43:54.599
and thank you for trying to help put that into

714
00:43:54.599 --> 00:43:57.239
a way that's understandable for everybody.

715
00:43:57.840 --> 00:44:00.719
But anything you make sorry, I didn't mean oh.

716
00:44:00.599 --> 00:44:03.000
No, sorry, I was just gonna say, like, yeah, that's

717
00:44:03.079 --> 00:44:05.880
kind of the basis of what I guess what I'm

718
00:44:05.920 --> 00:44:08.320
trying to get at is, like we we need to

719
00:44:08.360 --> 00:44:13.079
start using numbers and information and like statistical analysis or

720
00:44:13.159 --> 00:44:16.639
data analysis or whatever as the basis of our ideas

721
00:44:17.679 --> 00:44:20.880
towards the subject instead of the other way around, right like,

722
00:44:21.039 --> 00:44:25.719
just like we need to have something more substantial to

723
00:44:25.760 --> 00:44:28.760
start forming our ideas. And that's what I'm really hoping

724
00:44:28.920 --> 00:44:31.960
to do, Like, I'm really hoping that I can present

725
00:44:32.000 --> 00:44:35.079
this information and that you know, the data set is available,

726
00:44:35.119 --> 00:44:39.320
so you know, people can go through it, you know,

727
00:44:39.440 --> 00:44:43.360
and see what they can find out. But that's you know,

728
00:44:43.440 --> 00:44:46.480
a pretty big reason why I started this was because

729
00:44:46.760 --> 00:44:48.800
I was just I was hearing a lot of ideas

730
00:44:48.840 --> 00:44:51.840
and thoughts and things, but I wasn't seeing a lot

731
00:44:51.840 --> 00:44:56.320
of information to back up statements. So yeah, at least

732
00:44:56.360 --> 00:45:00.920
with at least with the data. You know, it's something, right, it's.

733
00:45:00.760 --> 00:45:04.400
Yeah, something I wouldn't cheapen what you're doing. And you

734
00:45:04.440 --> 00:45:07.559
did make one valid point, is you saw what you

735
00:45:07.679 --> 00:45:12.119
wanted to know and instead of complaining or crying or

736
00:45:12.199 --> 00:45:16.360
making shit up, sorry, you took the raw data and said, Okay,

737
00:45:16.400 --> 00:45:20.320
does this match my hypothesis? And that's that's the best

738
00:45:20.400 --> 00:45:23.199
kind of science. That's like Sean said earlier, is you know,

739
00:45:23.480 --> 00:45:25.920
I've seen the difference from when he had a sighting

740
00:45:25.960 --> 00:45:28.360
to when he didn't have a sighting, on how he

741
00:45:29.280 --> 00:45:32.519
handles witnesses, how he handles facts, how he handles a

742
00:45:32.519 --> 00:45:36.119
lot of things. I also, I've changed my opinion on

743
00:45:36.639 --> 00:45:39.519
how I feel about whether it's a creature. My opinion

744
00:45:39.559 --> 00:45:43.360
has never varied from it's either completely alive or we've

745
00:45:43.360 --> 00:45:45.280
been wasting seventy five years.

746
00:45:45.719 --> 00:45:47.039
Do you know what I mean, It's one or the other.

747
00:45:47.320 --> 00:45:50.639
But when Sean had a sighting, to listen to him

748
00:45:50.679 --> 00:45:52.679
and to see what he did, and to see how

749
00:45:52.719 --> 00:45:56.360
he's changed and how he does things, I believe more

750
00:45:56.599 --> 00:46:00.000
in the possibility of a creature than I did before

751
00:46:00.079 --> 00:46:03.800
for that because I trust in him, and I trust

752
00:46:03.840 --> 00:46:06.719
in what you're saying, because you've got a book that

753
00:46:06.840 --> 00:46:08.719
has the data if I want to look it up

754
00:46:08.760 --> 00:46:11.360
and read it, which you can ask for. Or I

755
00:46:11.360 --> 00:46:13.400
get mad at all kinds of things from the internet,

756
00:46:13.480 --> 00:46:16.159
like they say, blah blah blah this the this guy said,

757
00:46:16.159 --> 00:46:16.800
blah blah blah.

758
00:46:16.840 --> 00:46:19.719
Okay, where's the quote? Oh, I don't have any shut up?

759
00:46:20.039 --> 00:46:22.519
Okay, we done.

760
00:46:22.760 --> 00:46:25.280
But I just wanted I wanted to thank you for

761
00:46:25.400 --> 00:46:28.800
seeing a problem that didn't fit what you needed and

762
00:46:28.840 --> 00:46:31.760
then looking and making sure that the evidence fit it,

763
00:46:31.840 --> 00:46:33.920
not that you fit it to the evidence.

764
00:46:36.519 --> 00:46:39.960
Yeah, I'm happy, happy to very happy to do that

765
00:46:40.880 --> 00:46:43.280
because I just like I respect for that.

766
00:46:43.360 --> 00:46:46.840
I'm not you know, that's I wish I saw more

767
00:46:46.840 --> 00:46:47.800
of it in the community.

768
00:46:49.079 --> 00:46:53.159
I really appreciate that because it's definitely definitely needed. We

769
00:46:53.199 --> 00:46:56.840
need more of this, and you know, I just I

770
00:46:56.880 --> 00:46:59.320
hope to help in any way that I can, like

771
00:46:59.599 --> 00:47:03.960
just make more accessible or make it easier to interpret

772
00:47:04.119 --> 00:47:06.840
or whatever. Like, I'm always happy to answer data questions

773
00:47:06.880 --> 00:47:08.639
and stuff too, if people ever have them, Like, I'm

774
00:47:08.639 --> 00:47:10.679
always happy to go dig through the data sent and

775
00:47:10.719 --> 00:47:15.159
see what comes up. But yeah, I really really hope

776
00:47:15.199 --> 00:47:18.320
that that's what I'm put out there at least, is

777
00:47:18.360 --> 00:47:19.280
that kind of thinking.

778
00:47:19.760 --> 00:47:23.920
Yeah, well, you know what I have. I have a

779
00:47:24.000 --> 00:47:26.440
question here, and I'm going to kind of take this

780
00:47:27.639 --> 00:47:30.800
conversation or a whole new area here. We've been talking

781
00:47:30.840 --> 00:47:33.519
a lot about data. We've been talking a lot about

782
00:47:34.159 --> 00:47:38.960
you know, going through it and you know, analyzing it.

783
00:47:39.960 --> 00:47:43.599
Let's talk about something completely different. Have you had any

784
00:47:43.800 --> 00:47:47.400
experiences and have you done any field research. Have you

785
00:47:47.480 --> 00:47:49.480
been out in the in the field and tell us

786
00:47:49.480 --> 00:47:49.920
about it.

787
00:47:50.679 --> 00:47:55.280
Yeah, so I would say, I the field work is

788
00:47:55.280 --> 00:47:57.159
something that I really want to get into. I just

789
00:47:57.199 --> 00:48:01.960
haven't had really an opportunity. I will say though, that

790
00:48:02.039 --> 00:48:06.760
my my parents own a farm in Georgia, and every

791
00:48:06.760 --> 00:48:09.119
time we go back to visit, I'm basically in the woods,

792
00:48:09.159 --> 00:48:11.679
like twenty four to seven. Because I have had some

793
00:48:12.679 --> 00:48:16.400
weird things happen there. I can't definitively say that it

794
00:48:16.519 --> 00:48:20.880
was you know, the experiences were due to sasquatches, but

795
00:48:21.000 --> 00:48:25.039
also I have no idea, you know, what it was.

796
00:48:25.760 --> 00:48:29.880
Everything was auditory. My dad did see a big, a

797
00:48:29.880 --> 00:48:31.880
big dude though, running out of our barn once, so

798
00:48:31.920 --> 00:48:36.039
that was interesting. But you know, he can't he can't

799
00:48:36.199 --> 00:48:39.119
say for sure that it was a sasquatch. But you know,

800
00:48:39.159 --> 00:48:44.119
we've had We've had some weird stuff. Probably the weirdest

801
00:48:44.119 --> 00:48:49.119
thing that I've had happen is I woke up one

802
00:48:49.199 --> 00:48:53.480
night and I heard what sounded. The only way I

803
00:48:53.480 --> 00:48:56.199
can describe it is like it was a super demented turkey,

804
00:48:56.639 --> 00:48:59.000
Like I know, that's so weird, but it sounded like

805
00:48:59.039 --> 00:49:01.920
a really demented turkey gobble with like a horse snort

806
00:49:02.000 --> 00:49:06.440
at the end of it. It was so bizarre. And

807
00:49:06.920 --> 00:49:11.920
along with this, I heard very distinctive bipedal running in

808
00:49:11.960 --> 00:49:16.440
the woods, just back and forth in the woodline, and

809
00:49:16.480 --> 00:49:20.840
I'm hearing this through my wall and I'm like, I

810
00:49:20.840 --> 00:49:22.519
don't know what this is. I'm looking out my window.

811
00:49:22.599 --> 00:49:25.400
I can't see anything. My dogs are totally silent, which

812
00:49:25.440 --> 00:49:29.440
was weird. And it was just a very odd experience.

813
00:49:29.480 --> 00:49:32.280
And that went on for roughly like five to seven

814
00:49:32.320 --> 00:49:34.760
minutes and then it just stopped. Never heard it again.

815
00:49:35.480 --> 00:49:39.519
Oh wow, So it's just like very weird like auditory stuff.

816
00:49:39.559 --> 00:49:42.519
But again I can't I cannot at all say that

817
00:49:42.519 --> 00:49:47.920
that was the product of a sasquatch. But yeah, so.

818
00:49:48.440 --> 00:49:51.239
Yeah, I was trying to get out to the I

819
00:49:51.280 --> 00:49:53.239
would ask one question, how many.

820
00:49:53.079 --> 00:49:57.400
Dogs were there involved two?

821
00:49:58.119 --> 00:50:01.960
I had two outside dogs that barked at everything. And

822
00:50:02.039 --> 00:50:05.840
I remember sitting there thinking, this is so weird that

823
00:50:05.880 --> 00:50:09.320
they're not barking because they always bark. And then it

824
00:50:09.360 --> 00:50:12.400
turns out that that's, you know, that's something I keep

825
00:50:12.480 --> 00:50:16.039
up with in the data set. That's pretty common. Well,

826
00:50:16.079 --> 00:50:19.000
I hesitate to say common. It shows up more than

827
00:50:19.039 --> 00:50:23.800
you would think, especially in the Class A sightings. So yeah,

828
00:50:24.800 --> 00:50:25.119
I think.

829
00:50:25.400 --> 00:50:30.079
We've had discussions in the past about how animals react

830
00:50:31.119 --> 00:50:33.960
to different sightings, and I think that that's something that's

831
00:50:34.079 --> 00:50:37.440
interesting to put in the data as well. You get

832
00:50:37.440 --> 00:50:41.400
some dogs at that'll hel and you know, go running

833
00:50:41.440 --> 00:50:44.800
off and try to attack whatever's out there. You get

834
00:50:44.800 --> 00:50:49.840
other ones that big mean, you know, dogs that come

835
00:50:50.639 --> 00:50:52.880
running back with their tail between their legs, And I

836
00:50:53.440 --> 00:50:57.920
do think that that's possibly an important piece of data

837
00:50:58.000 --> 00:50:59.440
that could be included as well.

838
00:51:00.480 --> 00:51:02.599
Yeah, it's definitely something that I'm keeping up with. I

839
00:51:02.639 --> 00:51:05.559
have calls for it in the data set, you know,

840
00:51:05.599 --> 00:51:08.239
I just haven't run numbers on it. I should do

841
00:51:08.280 --> 00:51:12.559
that though, I probably have enough a large enough sample

842
00:51:12.599 --> 00:51:16.280
size at this point to look into that. Yeah, I

843
00:51:16.280 --> 00:51:18.119
can do that. I can run some numbers.

844
00:51:18.440 --> 00:51:20.920
So so one last question about the field research. With

845
00:51:21.039 --> 00:51:25.360
everything that you know from the data, when would you

846
00:51:25.480 --> 00:51:29.599
think the best time of year to be out in

847
00:51:29.639 --> 00:51:31.280
the field doing research would be?

848
00:51:32.039 --> 00:51:37.199
Yeah, So that question gets tricky because when we're looking

849
00:51:37.199 --> 00:51:40.679
at these patterns in the data, it's difficult to say

850
00:51:40.840 --> 00:51:45.519
if the patterns are due to you know, ecological reasons

851
00:51:45.880 --> 00:51:50.000
or a biological reason, or if it's due to you know,

852
00:51:50.159 --> 00:51:53.079
human patterns. So in the data set, there is an

853
00:51:53.119 --> 00:51:58.400
overwhelming majority of summer and fall class A sightings. And

854
00:51:58.840 --> 00:52:01.159
you know, as we know, this up really well with

855
00:52:01.480 --> 00:52:05.239
when humans are getting out you know outside, they're camping,

856
00:52:05.280 --> 00:52:09.880
they're hiking more, and they're hunting, especially in the fall. Actually,

857
00:52:09.920 --> 00:52:12.599
just read a paper the other day that like this

858
00:52:12.760 --> 00:52:14.880
you would think be intuitive, but you know, there's got

859
00:52:14.920 --> 00:52:17.519
to be a paper on it. You know, humans are

860
00:52:17.519 --> 00:52:20.400
more likely to be in remote places, they go further

861
00:52:20.519 --> 00:52:23.360
out into remote places during the fall versus any other

862
00:52:23.400 --> 00:52:26.480
time of the year, you know, because they're hunting and

863
00:52:26.480 --> 00:52:31.440
they're camping and whatever. So it's hard to say when

864
00:52:31.480 --> 00:52:34.280
the best time is. I will say there's a pretty

865
00:52:35.039 --> 00:52:38.519
large lack of sightings in the springtime, which is odd

866
00:52:38.559 --> 00:52:41.599
when you're looking at things from like a an animal

867
00:52:42.199 --> 00:52:45.320
kind of perspective, because usually they're you know, recovering from

868
00:52:45.320 --> 00:52:48.360
winter and they're foraging and they're out and about. So

869
00:52:48.400 --> 00:52:51.199
that's kind of interesting in itself and almost more interesting

870
00:52:51.239 --> 00:52:54.719
to me than the big spike that we have in

871
00:52:54.760 --> 00:52:58.920
the summer fall. So yeah, it gets it gets hard.

872
00:52:59.039 --> 00:53:01.239
It gets hard to say like when the best time

873
00:53:01.280 --> 00:53:03.840
to go is, because we don't know if these patterns

874
00:53:03.880 --> 00:53:07.519
are due to you know the animals themselves or due

875
00:53:07.559 --> 00:53:08.480
to people.

876
00:53:12.079 --> 00:53:13.960
And Sean.

877
00:53:15.679 --> 00:53:18.840
We do have a couple of questions from Scott on

878
00:53:19.079 --> 00:53:23.400
the from our patreon. Scott asks, what are key data

879
00:53:23.440 --> 00:53:27.719
points that researchers and investigators should gather related to settings

880
00:53:27.760 --> 00:53:30.840
or encounters that would help build better databases of information.

881
00:53:31.599 --> 00:53:32.440
That's one question.

882
00:53:33.079 --> 00:53:37.280
So definitely if if you can get a complete date

883
00:53:37.480 --> 00:53:41.360
for the encounter, that's super helpful. We can derive a

884
00:53:41.400 --> 00:53:46.320
lot of information from that, and particularly like environmental information

885
00:53:47.039 --> 00:53:51.679
lat moms are super helpful, and I think too if

886
00:53:51.719 --> 00:53:56.719
we can consistently gather data as well on like the

887
00:53:56.760 --> 00:54:01.320
witnesses occupation, how comfortable they are in the woods as well.

888
00:54:01.920 --> 00:54:04.880
Those are two things that I've been looking into recently

889
00:54:05.599 --> 00:54:07.800
that' kind of piqued my interest to see if there's,

890
00:54:07.840 --> 00:54:11.159
you know, are there any inherent differences between the sightings

891
00:54:11.440 --> 00:54:15.280
from people who are highly experienced in the woods versus

892
00:54:15.320 --> 00:54:20.280
those who are not things like that. So I would

893
00:54:20.320 --> 00:54:25.559
say the probably those four things, And it really depends

894
00:54:25.559 --> 00:54:28.880
on your research question too, Like it depends on what

895
00:54:29.000 --> 00:54:33.719
you're wanting to know, because like the STATA set's never ending,

896
00:54:34.559 --> 00:54:36.679
and I'm like I'm trying to keep up with so

897
00:54:36.760 --> 00:54:39.519
many variables and I just want to know everything about

898
00:54:39.559 --> 00:54:41.519
all of them, so it's hard for me to really

899
00:54:41.559 --> 00:54:46.119
pinpoint like what to tell people to ask. So I

900
00:54:46.119 --> 00:54:48.400
do think to a certain extent it does come down to,

901
00:54:48.800 --> 00:54:51.679
you know, personal preference of what you're wanting to get

902
00:54:51.719 --> 00:54:56.519
out of the experience. But yeah, I hope that answers

903
00:54:56.800 --> 00:54:57.320
a little bit.

904
00:55:01.159 --> 00:55:04.239
And then a second question, and what ways do you

905
00:55:04.320 --> 00:55:08.000
feel the use of AI is beneficial to the Bigfoot

906
00:55:08.039 --> 00:55:09.719
community and where is it detrimental?

907
00:55:10.360 --> 00:55:14.000
Yeah, so AI has actually been something I'm really interested in,

908
00:55:14.760 --> 00:55:16.840
very interested in AI and how to apply it to

909
00:55:17.079 --> 00:55:20.519
not only use tasquatch research, but just in general. I

910
00:55:20.559 --> 00:55:24.280
actually have a few videos on YouTube about this as well.

911
00:55:24.840 --> 00:55:26.920
How we can be applying it, how we shouldn't be

912
00:55:26.960 --> 00:55:30.440
applying it, which is almost more important than like how

913
00:55:30.480 --> 00:55:33.679
to apply it. The ways that I think it's going

914
00:55:33.719 --> 00:55:38.559
to be very beneficial is in its ability to kind

915
00:55:38.599 --> 00:55:43.800
of just make our make our work processes more efficient.

916
00:55:44.280 --> 00:55:47.480
So there's a couple of apps that I really like

917
00:55:47.559 --> 00:55:50.400
to use that are like text to speech and they

918
00:55:50.440 --> 00:55:53.880
also automatically grab like location data and time and like

919
00:55:54.039 --> 00:55:59.599
timestamps and whatnot. And you know, it obviously makes going

920
00:55:59.679 --> 00:56:04.079
through texts a lot easier if you know how to

921
00:56:04.159 --> 00:56:06.639
kind of mess with it, and it can really grab

922
00:56:06.679 --> 00:56:10.440
out information very well from text, especially depending on the

923
00:56:10.440 --> 00:56:13.480
model that you're using, you know, because different models are

924
00:56:13.519 --> 00:56:16.880
optimized for different things. Things we should not be using

925
00:56:17.519 --> 00:56:22.679
AI for is data analysis. We shouldn't be sending raw

926
00:56:22.760 --> 00:56:27.440
data right like through AI. And that's something that I'm

927
00:56:27.480 --> 00:56:30.880
starting to see and it's making me nervous because, like,

928
00:56:31.199 --> 00:56:33.719
at the end of the day, the thing that we

929
00:56:33.800 --> 00:56:37.039
call AI or just large language models, they're just text

930
00:56:37.039 --> 00:56:42.679
predators and so they can barely count like how many

931
00:56:43.320 --> 00:56:46.360
a's are in a word or whatever. Like if you

932
00:56:46.400 --> 00:56:49.920
ask it to count something, it's usually wrong. So you know,

933
00:56:50.039 --> 00:56:53.320
asking it to do data analysis is just going to

934
00:56:53.360 --> 00:56:58.000
be detrimental. Also, asking it to identify patterns in data,

935
00:56:59.159 --> 00:57:02.800
it's not very good at that either. So you know,

936
00:57:03.159 --> 00:57:05.480
things like that I think we need to be really

937
00:57:05.480 --> 00:57:09.800
careful about. But for the most part, it should just

938
00:57:09.840 --> 00:57:11.480
be a tool and the tool belt. You know, it

939
00:57:11.519 --> 00:57:14.800
shouldn't be driving our research and doing our research for us,

940
00:57:14.840 --> 00:57:19.480
but it should be a supplement. I personally think, yeah,

941
00:57:19.480 --> 00:57:21.159
that's a really good question. I could go on about

942
00:57:21.159 --> 00:57:24.320
AI forever because I love it and I'm like really

943
00:57:24.360 --> 00:57:27.320
getting into like how to how to do like AI

944
00:57:27.400 --> 00:57:29.000
engineering and stuff like that.

945
00:57:29.599 --> 00:57:37.800
M gentlemen, any final thoughts or questions for Trestrial?

946
00:57:40.960 --> 00:57:44.519
I was gonna say, we have, between Shan and I,

947
00:57:45.159 --> 00:57:48.519
we have a lot of witness reports. You know that

948
00:57:48.519 --> 00:57:55.960
would be a class A that may be usable for

949
00:57:55.960 --> 00:57:59.280
for the data set? Is that something that we could

950
00:58:00.079 --> 00:58:04.639
email to you? Uh, the information? And what format to

951
00:58:04.719 --> 00:58:07.239
you generally like to take that? Is it you know

952
00:58:07.320 --> 00:58:09.440
in Excel or or how Yeah?

953
00:58:09.760 --> 00:58:13.280
So basically how I have things set up now my

954
00:58:13.719 --> 00:58:18.519
program that I have honestly a text file of the

955
00:58:18.679 --> 00:58:22.199
entire report for each report is the best. It depends

956
00:58:22.239 --> 00:58:25.800
on how how you haven't set up as is. But

957
00:58:26.159 --> 00:58:28.119
basically how my program runs is I just send in

958
00:58:28.159 --> 00:58:31.639
a report and it extracts, okay, all the information. So

959
00:58:32.519 --> 00:58:35.920
we can definitely chat about that.

960
00:58:36.599 --> 00:58:40.599
We do have one question that's sneaked in from our

961
00:58:40.719 --> 00:58:43.639
executive producer, Brian Corbin. So we have to ask this question,

962
00:58:44.480 --> 00:58:48.599
and the question is can Terrestrial discuss what project she

963
00:58:48.679 --> 00:58:51.800
has that works with Darby Orchid at North Carolina State.

964
00:58:54.079 --> 00:58:57.280
I don't think I'm at liberty just say quite yet,

965
00:58:59.400 --> 00:59:05.559
but yeah, maybe in another month or two I need

966
00:59:05.559 --> 00:59:09.239
to chat with him.

967
00:59:09.360 --> 00:59:12.360
Very good, Tresture, Thank you so much for spending some

968
00:59:12.400 --> 00:59:15.360
time with us before you head out. Where can folks

969
00:59:15.400 --> 00:59:18.199
find out more about the Sasquatch Data Project and perhaps yourself?

970
00:59:18.760 --> 00:59:22.239
Yeah, so I post the most on Instagram. My handle

971
00:59:22.280 --> 00:59:25.280
there is just at Sasquatch Data. It's actually my handle

972
00:59:25.320 --> 00:59:28.760
on everything is just at Sasquatch Data. But yeah, I'm

973
00:59:28.760 --> 00:59:33.239
on Instagram, Facebook, TikTok, YouTube, all that fun stuff. I

974
00:59:33.280 --> 00:59:35.920
try to post on YouTube like at least once a month,

975
00:59:36.000 --> 00:59:38.039
but on all my other channels I try to post

976
00:59:38.079 --> 00:59:41.719
weekly with data investigations and updates. You can also check

977
00:59:41.719 --> 00:59:45.519
out my research at Sasquatch Data Project dot com and

978
00:59:45.559 --> 00:59:47.840
if you want to reach out, my email is contact

979
00:59:47.880 --> 00:59:50.559
at Sasquatch Data Project dot com.

980
00:59:50.679 --> 00:59:52.840
Very good, very good, Thanks so much for spending some

981
00:59:52.880 --> 00:59:58.639
time with us, folks, you much, Thank you so much. Folks,

982
00:59:58.639 --> 01:00:02.440
you've been listening to the Sasquatch experience here on Anomalous

983
01:00:02.599 --> 01:00:06.960
Entertainment on YouTube, Facebook, wherever you stream us like Lee,

984
01:00:07.320 --> 01:00:09.480
like us, subscribe to us if you want. I can't

985
01:00:09.519 --> 01:00:11.239
say it's that great to subscribe us all the time.

986
01:00:11.599 --> 01:00:14.679
But also rate us and review us. That's very important

987
01:00:15.400 --> 01:00:17.760
for us to get that feedback. And on that note, folks,

988
01:00:17.800 --> 01:00:20.239
thank you. We'll see you in two weeks. And for

989
01:00:20.440 --> 01:00:22.039
those of you that are going to join us at

990
01:00:22.039 --> 01:00:25.000
the Pennsylvania Camping Adventure, we look forward to hanging out

991
01:00:25.000 --> 01:00:28.280
with you. Thank you again. And hey, one more thing,

992
01:00:28.440 --> 01:00:31.760
Squatch out hunger folks, Sasquatch Experience dot com. Click on

993
01:00:31.800 --> 01:00:34.840
the banner, help us feed some people and we'll see

994
01:00:34.840 --> 01:00:41.360
you next time. You've been listening to The Sasquatch Experience.

995
01:00:41.880 --> 01:00:49.960
Please rate and review wherever this podcast is consumed. For

996
01:00:50.039 --> 01:01:05.960
more information, please go to our website, Sasquatch Experience dot com.

997
01:01:06.639 --> 01:01:07.920
Keep on watching