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Speaker 1: Giving in and cook Craig Anthony Halp of The You Project.

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Speaker 1: Possibly I've been rolled with the punches. Who fucking knows?

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Speaker 1: It could be a share a co share, Hi tiv.

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Speaker 2: Hi Harps, I dare say it will it's been a

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Speaker 2: while since your dulcet tones of grace, the role with

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Speaker 2: the punches platform. Where you've been, bro, I've.

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Speaker 1: Been, I've been. I've been doing grown up things like

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Speaker 1: a big boy. I've been like a big boy doing

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Speaker 1: the PhD, big boy PhD, trying to interpret all the results.

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Speaker 1: And do you want me to give you a quick

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Speaker 1: snapshot on where I'm at? Yeah, sure, my brain it's

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Speaker 1: already so I've done it. No, nothing, it's not. I've

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Speaker 1: done all my research, which I should have because I'm

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Speaker 1: five years in, so hurry the fuck up, you old prick.

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Speaker 1: All my studies have then done, All the data's in,

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Speaker 1: all the interpretation is nearly done, or what they call

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Speaker 1: academic milestones have been ticked off for of those. I'm

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Speaker 1: writing papers. I'm writing multiple papers. I'm writing a systematic

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Speaker 1: literature review. I'm writing two maybe three empirical papers. What

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Speaker 1: that means is when you do your own research, that

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Speaker 1: is your own new research. You're adding new kind of

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Speaker 1: stuff to the world of science, so you're doing empirical

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Speaker 1: studies and then reporting on that. I'm doing that, and

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Speaker 1: I just spent the last two hours going through the

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Speaker 1: first draft of one of my papers, which is both

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Speaker 1: exciting but also makes you want to punch yourself in

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Speaker 1: the face. So that is where I'm at. And I

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Speaker 1: think I may even like I've never thought I have

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Speaker 1: ADHD and I probably don't.

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Speaker 2: I think you might.

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Speaker 1: I don't know, but you know how, like some things

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Speaker 1: I am I can get engrossed in, right, then there

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Speaker 1: are other things and it's like the actual focus of

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Speaker 1: my researchers, you know, which is metaacricy metaperception, understanding how

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Speaker 1: others see you and essentially how to measure that and

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Speaker 1: how to like what are the things that determine how

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Speaker 1: good somebody is at understanding how they are seen, perceived,

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Speaker 1: experienced by other people, What are the variables, what are

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Speaker 1: the cognitive traits, like the kind of the brain things,

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Speaker 1: and what are the emotional kind of attributes that influence

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Speaker 1: the like in day to day real world conversations out

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Speaker 1: out and about doing life. It's fucking fascinating, right, But

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Speaker 1: when it comes down to looking at is the data

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Speaker 1: analysis from you know study too, and here's here's a

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Speaker 1: fucking Excel spreadsheet with fifteen million numbers. And then me

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Speaker 1: and the sixty one year old brain.

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Speaker 3: Are like, oh ah, trying to figure out what all

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Speaker 3: that means and then to put it into real you know,

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Speaker 3: to figure out really what it means and what the

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Speaker 3: data tells you, and then how to write about that,

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Speaker 3: and then to figure out what the other research tells you, Like,

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Speaker 3: what is all the other research in this this kind

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Speaker 3: of cognitive metacognitive metaperceptive, metaaccurate space.

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Speaker 1: What is that tell you? And is aligned? Does it disagree?

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Speaker 1: What hole are you feeling in the science?

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Speaker 2: And was anything wildly more different to prove than you thought? Like,

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Speaker 2: was anything harder or easier to prove or the way

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Speaker 2: you had to go about it?

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Speaker 1: Like the hardest part for me is not like the

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Speaker 1: funny thing is And I've said this before because I

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Speaker 1: really I was fucking clueless, you know, I got asked

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Speaker 1: if I was. I didn't get monach, didn't stand out

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Speaker 1: and go hey, we would love you to do a PhD.

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Speaker 1: But I did some work for them for the brain

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Speaker 1: Brain Park kind of group, which is the Neuroscience Neuropsychology

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Speaker 1: Psychology Lab, and I went in to do a talk

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Speaker 1: to them about just which was hilarious because I was

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Speaker 1: the least qualified in terms of academic you know, I

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Speaker 1: had an undergrad degree, and I'm talking to everyone who

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Speaker 1: at the very least is a PhD student and you know,

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Speaker 1: professors and department leaders. But they were fascinated with the

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Speaker 1: way that I do my work, and because I essentially

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Speaker 1: help people change, you know, physically, mentally, emotionally, practically, behaviorally,

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Speaker 1: and they're like, how do you do that? What's kind

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Speaker 1: of watch your protocol? And and I'm like, what's a protocol?

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Speaker 1: You know a little bit, because yes, of course I

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Speaker 1: have a I had, you know, a mild academic background.

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Speaker 1: I had a degree in exercise science and a bit

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Speaker 1: of other experience and other stuff. But you know, really

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Speaker 1: it's like you're learning, You're not when you do a

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Speaker 1: PhD in psychle or neuropsych you're not really learning as

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Speaker 1: much about the mind as you are about how to

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Speaker 1: do research at that level. And so of course I've

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Speaker 1: learned more about you know, the specifics of metaaccuracy and

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Speaker 1: meta perception, and I can tell you more than I

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Speaker 1: could have told you five years ago. But you know,

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Speaker 1: five years ago, I still understood the nuts and bolts

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Speaker 1: of what I now understand to a a level. And

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Speaker 1: I did that intuitively and instinctively over time, talking to

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Speaker 1: thousands of people, realizing that how I see me isn't

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Speaker 1: how they see me. And so it's important that I

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Speaker 1: do have an insight into what the Craig experience is

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Speaker 1: like for the rest of the world, not for my

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Speaker 1: ego or my security, but so that I can build connection,

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Speaker 1: rapport and trust, and solve problems together, and work as

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Speaker 1: part of a team together, and resolve conflict, and to

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Speaker 1: be an effective podcast, to teach, a coach, mentor corporate speaker.

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Speaker 1: All that because if you stand in front of a group,

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Speaker 1: whether it's even a group of two or three or

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Speaker 1: a group of a thousand, and you've got no idea

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Speaker 1: what the Craig or the Tiff or the U experience

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Speaker 1: is like for the rest of the room or the

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Speaker 1: podcast audience in this case, then you're guessing, and you're

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Speaker 1: just as likely to create disconnection as connection. But everyone's

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Speaker 1: goal is connection. Everyone's goal is understanding, you know, But

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Speaker 1: you might be creating more confusion than anything. But you

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Speaker 1: don't fucking know. So, But I mean it's been great

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Speaker 1: for me because I'm not a natural academic, I'm a

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Speaker 1: pro academic, and so to make me learn this new

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Speaker 1: language and this new protocol and this new universe, like

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Speaker 1: it's a fucking universe where it's my analogy was the

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Speaker 1: first year, it's like going to Russia and you know

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Speaker 1: that you're not dumb, but you feel dumb because everyone

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Speaker 1: speaks Russian and you don't, and people are talking to you,

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Speaker 1: and even three six months in you're getting you know,

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Speaker 1: two in ten words, so you're piecing together what they're saying.

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Speaker 1: But they literally use a language. I mean literally a

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Speaker 1: language like you know, words and phrases and constructs and

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Speaker 1: concepts that not only don't you use, you've never heard of, right,

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Speaker 1: And so now you're learning this new language as well

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Speaker 1: as learning how to do the highest level of research.

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Speaker 1: And then you've got to write papers which are going

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Speaker 1: to be published in academic journals and you know all

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Speaker 1: of that. So it's really yeah, I've I've learned a

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Speaker 1: fair bit about obviously the focus of my research, but

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Speaker 1: also more I've learned about how to do a PhD

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Speaker 1: and how to do that kind level of research?

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Speaker 2: Were there any concepts that to you felt really obvious

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Speaker 2: and easy to explain and clear, but then had you

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Speaker 2: completely stumped on how do I put together any how

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Speaker 2: do I have a way to research improve this point

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Speaker 2: or theory?

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Speaker 1: Yeah? So, I mean what you know or what you

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Speaker 1: think you know does not fucking matter at all. Like

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Speaker 1: I could go, oh, yeah, but I've done sixty thousand

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Speaker 1: personal training sessions. That's sixty thousand conversations with thousands of

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Speaker 1: people in a range of different scenarios and situations. So

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Speaker 1: I've got forty years of fucking experience at the cold

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Speaker 1: face of interpersonal and they're like, yeah, big deal, what's

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Speaker 1: the research say, It's like, yeah, that's nice. Next it

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Speaker 1: doesn't matter, Like it doesn't matter in the sense that

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Speaker 1: your experience, by the way, outside of this particular world

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Speaker 1: that we're talking about, it is very important. Like your experience,

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Speaker 1: your ideas, your insights, your understanding, your conversations, your real

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Speaker 1: world learning on a practical life kind of reality or

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Speaker 1: in a practical life reality or level, it really matters

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Speaker 1: because it's appliable, it's usable, it's practical, right, But in

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Speaker 1: an academic environment. When you are bringing science or new

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Speaker 1: research into the world, it doesn't matter what you think.

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Speaker 1: It matters what you can prove and what the data says,

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Speaker 1: and what the research tells us and what your experiments,

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Speaker 1: for one of the better term show us. That's what matters. Now,

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Speaker 1: what you think and what you've experienced and what you

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Speaker 1: believe can inform your research. That is the way that

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Speaker 1: you create design your studies, or the kinds of questions

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Speaker 1: that you ask or the hypotheses that you form. But

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Speaker 1: you know, what you think you know is irrelevant in

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Speaker 1: terms of the final product. It's all about what the

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Speaker 1: data says. And yeah, and really you are studying such

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Speaker 1: a specific thing, you know, in it's like I've said

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Speaker 1: this probably fifty times, so I apologize, But I'm studying

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Speaker 1: a drop of water in an ocean of human behavior.

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Speaker 1: Like there are so many variables and so many factors

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Speaker 1: and so many components and jigsaw piece puzzles to the

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Speaker 1: human experience from a psychological, emotional, and sociological point of

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Speaker 1: view that you think, oh well, ah, I understand. Saying

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Speaker 1: I understand how the mind works is like saying I

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Speaker 1: understand how the universe works.

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Speaker 2: Like it.

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Speaker 1: I truly don't think anyone fully understands the mind. And

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Speaker 1: I think I naturally, like I'm not good. I never

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Speaker 1: say I'm good at anything, but I think I naturally

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Speaker 1: have a reasonable grasp of human behavior and you know,

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Speaker 1: metaperception and cognition, all that shit in the mind. But

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Speaker 1: I still think, of all there is to know, I

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Speaker 1: know nearly fucking nothing. So understanding the mind is pretty

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Speaker 1: much an impossibility if we're talking about totally understanding the mind,

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Speaker 1: and also even you know, interestingly proving that there is

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Speaker 1: a mind, you know. And the thing with psychology is

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Speaker 1: that it is. And this is going to now sound

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Speaker 1: like I'm throwing my own field under the bus, but

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Speaker 1: it's probably the hardest, if not the messiest, if not

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Speaker 1: the most unreliable science, because you know, when we think about,

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Speaker 1: like all of the stuff that I or most of

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Speaker 1: the stuff that I did, was using a range of

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Speaker 1: different psychometric tools for testing, you know, scales and questionnaires

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Speaker 1: and all kinds of things, but it's all subjective self evaluation.

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Speaker 1: And as I've said to you many times, and I'll

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Speaker 1: shut up after this, but the problem with psychology is

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Speaker 1: that I could listeners, I could get Tiff to complete

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Speaker 1: a questionnaire which assesses her her overall let's say mental health,

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Speaker 1: or it's an insight or a tool to assess mental health,

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Speaker 1: or emotional health, or extraversion or introversion or conscientiousness or

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Speaker 1: you know whatever, all of these different factors or traits now,

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Speaker 1: and then I get all the data because Tif did

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Speaker 1: this protocol and filled out all of these answers, and

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Speaker 1: then I get it and I go, here's my data.

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Speaker 1: And then I do the same protocol with Tiff. A

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Speaker 1: week later. She's in a different headspace. She hasn't slept well,

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Speaker 1: she's a bit grumpy because the dog ate the cat,

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Speaker 1: and a whole lot of shit's going on. And I

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Speaker 1: get completely different data from the same human using the

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Speaker 1: same protocol. Now you don't get that typically in other sciences.

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Speaker 1: It's like if I measure your body composition today using

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Speaker 1: a reliable tool, and now I measure it tomorrow, I'm

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Speaker 1: going to get the same outcome. If if you know,

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Speaker 1: I if I drop some if I drop a bowling

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Speaker 1: ball in a vacuum, it's going to fall at the

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Speaker 1: same speed every time as is a feather. Right, there's consistency.

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Speaker 1: If I go all right, anatomy. Well, that bone in

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Speaker 1: the top of the it's today we call it the fema.

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Speaker 1: Guess what we call it the fucking fema tomorrow as well.

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Speaker 1: It's not going to be a humorous or a bloody

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Speaker 1: patella tomorrow. Like, there's consistency and reliability. But in in

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Speaker 1: the research of psychology, and this is not the right term,

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Speaker 1: but listeners will understand it. The measurement of the mind,

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Speaker 1: or the components of the mind, or the attributes of

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Speaker 1: the mind, it's at best messy.

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Speaker 2: If you had to allocate a percentage to the level

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Speaker 2: of inconsistency around around this research because of that reason,

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Speaker 2: what percentage would.

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Speaker 1: You Yeah, look, I really couldn't. But I'll answer that

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Speaker 1: with I'll talk around that. You know. So for example

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Speaker 1: that generally speaking, my research falls into the space of

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Speaker 1: self awareness, social awareness, situation. You know, it's an awareness

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Speaker 1: kind of piece. Now, even in academic literature, you will

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Speaker 1: not get a consensus on something as simple as self awareness.

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Speaker 1: It's not like, oh, here's the definition. Everyone uses this definition.

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Speaker 1: This is the go to. So depending on which field

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Speaker 1: of psychology, because there's different fields of course, you know,

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Speaker 1: social psychology and sports psychology and clinical psychology, and you

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Speaker 1: know that all the psych work they do in the

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Speaker 1: corporate space, Like, there's different areas of psychology, same field,

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Speaker 1: different areas, but that'll be defined differently in different contexts.

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Speaker 1: So there's a lot of convergence. So coming together in agreement,

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Speaker 1: there's probably just as much, if not more, divergence of

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Speaker 1: disagreement disparity, Like I don't know about that, but I

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Speaker 1: will say, you know, I was talking to Chris, who's

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Speaker 1: my senior supervisor, and you know that I was talking

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Speaker 1: about the oldest kind of reference to self awareness that

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Speaker 1: I could find anyway, is like two and a half

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Speaker 1: thousand years and it's Socrates who said the beginning of

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Speaker 1: wisdom is to know thyself. Right, that's self awareness. It's

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Speaker 1: like and he was talking two and a half thousand

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Speaker 1: years ago about basically to know yourself and understand yourself.

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Speaker 1: It is an indicator of wisdom, you know, if not intelligence.

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Speaker 1: And so it's been something that people have been thinking

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Speaker 1: about for a long time. But you know, I truly

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Speaker 1: believe and I'm not saying it because it's my research.

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Speaker 1: I think, you know, it's one of many interpersonal superpowers.

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Speaker 1: But if you can really understand how other people experience you,

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Speaker 1: or think of you, or perceive you, and then you

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Speaker 1: use that information in the right way, you use that understanding,

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Speaker 1: you use that knowledge in the right way, then you

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Speaker 1: can become much better at all things communication, problem solving,

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Speaker 1: leadership management, friendship, parenting, because you understand stand what they're

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Speaker 1: getting because we always look at the situation, conversation, negotiation

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Speaker 1: through our lens, but they're not looking through that lens.

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Speaker 1: So it's in our interest to, as you've heard me

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Speaker 1: say many times, to walk away from our window and

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Speaker 1: metaphorically try and have a peek through theirs, because it

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Speaker 1: doesn't matter if we agree or disagree, but to see

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Speaker 1: through their window is to have a level of awareness

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Speaker 1: and understanding that you don't when you are, you know,

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Speaker 1: thinking that everybody else thinks like you. We've spoken about

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Speaker 1: the false consensus effect. The false consensus effect which most

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Speaker 1: people are trapped in is they think that other people

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Speaker 1: think like them, which is broadly not true.

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Speaker 2: You have to make decisions on like when you get

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Speaker 2: into researching any topic or learning about something, into podcasts

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Speaker 2: and listening to experts, and now you're one of them,

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Speaker 2: and so I'm interested in because you get to these

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Speaker 2: crossroads where you have to make a decision on which

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Speaker 2: side of the belief you're going to lean towards. Were

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Speaker 2: there any of those crossroads that came up for you

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Speaker 2: that you felt biased pulling you in a way, that

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Speaker 2: logic was probably pulling you the other way, and we

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Speaker 2: were there areas that you had to kind of I

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Speaker 2: don't know.

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Speaker 1: Yeah, Look, I mean there are things that I naturally,

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Speaker 1: you know, I think a lot of things about this,

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Speaker 1: but to be able to unequivocally prove that again using

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Speaker 1: subjective assessment tools and psychometric tools that we have available,

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Speaker 1: it's really not that you are standing on top of

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Speaker 1: the academic you know, pullpit and screaming out to the

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Speaker 1: world this, Hey everyone, I've figured it out. So all

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Speaker 1: the other scientists and researchers before me, fuck them. This

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Speaker 1: is how the works. You're not doing that, you kind

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Speaker 1: of you're kind of telling them your best understanding of

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Speaker 1: what your research tells you, and your research is informed

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Speaker 1: by or guided by what you originally thought before you

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Speaker 1: started the research, right, what your questions or hypotheses were,

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Speaker 1: but also what other people in the field have found

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Speaker 1: or not found. So when you're doing a PhD for example,

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Speaker 1: especially in the psychology space, but most spaces. I've never

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Speaker 1: done mine outside of psych But I assume you know

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Speaker 1: your job is to build on existing science, Like what

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Speaker 1: do we already know? Yeah, well, don't do that, Greg,

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Speaker 1: We already know that. Or I might have a theory

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Speaker 1: that contradicts a current theory and I might disprove something,

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Speaker 1: or I might recognize a gap in you know, well

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Speaker 1: we haven't looked at this particular thing through this lens

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Speaker 1: or factoring in this variable. So we're going to do that, right, So, like,

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Speaker 1: do you want me to bore you for one minute?

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Speaker 1: I just bought up one of my papers. This is

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Speaker 1: the working tile, right, and this is very This is

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Speaker 1: quite understandable because this is just an abstract and this

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Speaker 1: is very much a work in progress. So the name

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Speaker 1: of this paper, don't get too excited. It's called gender

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Speaker 1: and Mental health as Determinants of meta Accuracy. So what

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Speaker 1: I'm doing in this particular paper is looking at the

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Speaker 1: way that mental health, positive or negative, can impact a

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Speaker 1: person's level of meta accuracy, in other words, how good

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Speaker 1: they are at predicting how other people see them, and

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Speaker 1: also the role of gender, so meta accuracy. So this

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Speaker 1: is this is the world's never heard. Yes, this is

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Speaker 1: the abstract. This is a work in progress. This will

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Speaker 1: probably change a bit, but this is what I was

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Speaker 1: working on before. And this is a five thousand word

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Speaker 1: paper about twenty pages at this point. Metaaccuracy, the ability

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Speaker 1: to infer how others perceive us, is a critical component

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Speaker 1: of effective social functioning and interpersonal relationships. This study explores

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Speaker 1: my study the intersection of mental health, gender, and metaaccuracy

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Speaker 1: within close relationships, focusing on how positive and negative mental

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Speaker 1: health states influence metaperception accuracy across personality traits using a

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Speaker 1: partner based correlational design. Ninety diads. That means ninety pairs

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Speaker 1: n equals one to eighty. That's the total number of

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Speaker 1: participants that many people completed self reports, partner ratings, and

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Speaker 1: metaperception assessments online. Now this is what nobody in the

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Speaker 1: world has heard, and so I could be fucking myself

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Speaker 1: up here. But anyway, results reveal, so this is very preliminary.

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Speaker 1: Results reveal that positive mental health enhances metaaccuracy for emotional

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Speaker 1: stability and openness. So, in other words, what that means

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Speaker 1: is your ability to predict. So if I say to

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Speaker 1: you tif one to five. How emotionally stable are you?

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Speaker 1: You go, I'm a four, and I predict you're a four,

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Speaker 1: then you're quite meta accurate regarding that particular trait. So

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Speaker 1: to openness, right, So I'll explain it briefly at the end.

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Speaker 1: With gender specific patterns, males showed greater accuracy for emotional ability,

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Speaker 1: while females exhibited greater accuracy for openness and conscientiousness. So

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Speaker 1: your ability to predict how other people see you tif

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Speaker 1: in terms of openness and conscientiousness. Females are typically, in

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Speaker 1: my research, better than that. Negative mental health, particularly stress,

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Speaker 1: consistently impaired meta accuracy affecting consciousness, conscientiousness, and emotional stability.

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Speaker 1: That is the prediction of those two traits in terms

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Speaker 1: of accuracy, with greater susceptibility observed among females. Depressions selectively

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Speaker 1: reduced emotional stability meta accuracy in male I know this

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Speaker 1: is complicated. These findings unscore the nuanced interplay between mental

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Speaker 1: health and gender in shaping social cognition, providing insights into

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Speaker 1: potential tailored interventions to improve relational and psychological well being.

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Speaker 1: Implications for theory, therapeutic practice, and future research on social

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Speaker 1: perception dynamics are discussed within the paper. So that's my

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Speaker 1: that's a snapshot of what the papers about.

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Speaker 2: Right, it's full of fascinating. It's pretty fascinating though.

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Speaker 1: Yeah, it's fucking amazing, right, And so the snap shot.

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Speaker 1: And I'm still like, I'm still sifting through the analysis

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Speaker 1: and the data, and so this could this could change,

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Speaker 1: So don't take this as gospel. But generally speaking that like,

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Speaker 1: sometimes you get data that doesn't really show anything one

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Speaker 1: way or the other. It doesn't show a positive or

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Speaker 1: a negative relationship, or it doesn't show a correlation between

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Speaker 1: this particular thing and that particular thing, right, But what

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Speaker 1: does seem to be showing up with this particular Remember

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Speaker 1: this is one study in a million billion studies, So

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Speaker 1: this is Craig study with one hundred and eighty people,

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Speaker 1: ninety diads, ninety pairs. It seems that women are better

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Speaker 1: at it. This is not a shocker. And also that

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Speaker 1: also that people with more positive mental health, So people

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Speaker 1: who are generally happier, more optimistic, more positive generally have

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Speaker 1: greater levels of better accuracy than people who have depression, anxiety,

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Speaker 1: and stress. So there's a scale called the DAS twenty

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Speaker 1: one which is DAS is depression anxiety stress and the

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Speaker 1: second S is scale Depression anxiety Stress Scale. So that's

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Speaker 1: one of the psychometric tools that I use. But yeah,

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Speaker 1: it's really interesting and you because what it does is

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Speaker 1: it takes out my opinion and my emotions, and all

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Speaker 1: it is is me kind of getting all of the

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Speaker 1: data data that we've collected and interpreting that as best

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Speaker 1: as we can. Having said that this is my and

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Speaker 1: this is not about my research or anyone in particularly.

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Speaker 1: But one of the problems with science, and I've said

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Speaker 1: this and you and I have alluded to this many times,

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Speaker 1: is that all scientists are human. All humans make mistakes,

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Speaker 1: all humans have bias, all humans have emotion. Humans want

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Speaker 1: to to an extent, be right right, And so this

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Speaker 1: is one of the things is to produce great science,

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Speaker 1: you really don't want to have an emotional investment in

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Speaker 1: the outcome because if I want a certain outcome, then

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Speaker 1: I'm not going to be completely objective.

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Speaker 2: Right.

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Speaker 1: So even when you go, well here's the objective data,

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Speaker 1: this is what the computer, this is what the analytics

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Speaker 1: spewed out using these different analysis programs, But then it's

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Speaker 1: down to the individuals to interpret that and share that

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Speaker 1: with the world. So I will say that, you know,

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Speaker 1: we need science, absolutely, and science is great, but science

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Speaker 1: is not perfect one because the protocols are not perfect,

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Speaker 1: the execution of the research is not perfect, the research

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Speaker 1: design is not perfect, and the people doing all the

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Speaker 1: science are not perfect. So I always think when we

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Speaker 1: say something, our science tells us. Firstly, when someone with

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Speaker 1: a broad fucking brush says science tells us already, I'm like,

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Speaker 1: that's bullshit, unless you can tell me the research, the researchers,

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Speaker 1: the studies, how many people were in it, what was

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Speaker 1: the risk of bias with that particular research? Was that

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Speaker 1: research funded by any organization? With some research, it's nearly

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Speaker 1: as high as ninety percent funded, depending on what field.

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Speaker 1: So if you know that your ability to keep doing

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Speaker 1: research is dependent on that company financing essentially your livelihood

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Speaker 1: and your study and your research, you don't want to

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Speaker 1: give them data that doesn't work for them commercially. And so,

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Speaker 1: of course, obviously nobody funds my research because gives a fuck,

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Speaker 1: and I don't want it. I don't want it to

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Speaker 1: be like I'm just genuinely interested in the outcome, you know,

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Speaker 1: And that's not saying my my research won't be flawed,

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Speaker 1: but I think it's important, you know, especially today there's

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Speaker 1: so much shit online with fucking influencers going oh, well

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Speaker 1: we know that if you eat that and you don't

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Speaker 1: do that and this is the result, and you're like, no,

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Speaker 1: that's that's just just because that's coming out of your face.

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Speaker 1: That doesn't mean it's true. That's just used saying words,

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Speaker 1: and you know, like most firstly, I'm literally getting towards

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Speaker 1: the end of my PhD, and I think even I'm

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Speaker 1: not a good source half the time.

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Speaker 2: So five years of research and you get to land

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Speaker 2: on proving this theory, then what because it takes five

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Speaker 2: years to prove the theory, and then how do you

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Speaker 2: move the needle to make it practical for us?

429
00:28:02,200 --> 00:28:04,720
Speaker 1: Yeah, that's great. So that's a great question. So for me,

430
00:28:04,920 --> 00:28:07,040
Speaker 1: I mean, I don't have any grand plans around this.

431
00:28:07,160 --> 00:28:10,639
Speaker 1: For me, even if all I got out of this

432
00:28:10,800 --> 00:28:13,080
Speaker 1: was learning how to study properly with I have, which

433
00:28:13,160 --> 00:28:16,000
Speaker 1: I have, and learning how to design a research project,

434
00:28:16,000 --> 00:28:18,840
Speaker 1: which I have, and then learning how to run studies

435
00:28:18,840 --> 00:28:21,800
Speaker 1: with humans and get ethical approval and assess risk of

436
00:28:21,880 --> 00:28:27,840
Speaker 1: bias and read fucking copious amounts of academic journal papers

437
00:28:27,880 --> 00:28:31,760
Speaker 1: and understand even if that's all I get, it's been worthwhile, right,

438
00:28:31,840 --> 00:28:36,960
Speaker 1: So selfishly that are But on a more practical level,

439
00:28:38,240 --> 00:28:42,640
Speaker 1: it's okay. If I'm being completely honest. Does it hurt

440
00:28:42,640 --> 00:28:44,520
Speaker 1: for me to rock up to a company and be

441
00:28:44,600 --> 00:28:47,960
Speaker 1: doctor Craig Harper with a PhD in psychology? Of course

442
00:28:48,000 --> 00:28:50,719
Speaker 1: that doesn't hurt. That's not my reason, right, But that

443
00:28:50,760 --> 00:28:53,720
Speaker 1: doesn't hurt. Of course. We're just talking about perception and

444
00:28:53,800 --> 00:28:59,480
Speaker 1: brand and you know, commercial viability. So Craig, the bloke

445
00:28:59,520 --> 00:29:01,240
Speaker 1: who used to left heavy shit and be a fat

446
00:29:01,280 --> 00:29:06,240
Speaker 1: guy versus you know, this guy with a PhD in psychology.

447
00:29:06,240 --> 00:29:09,360
Speaker 1: Probably that gives me some kind of slight advantage. Maybe

448
00:29:09,400 --> 00:29:14,120
Speaker 1: maybe not, But I truly believe this idea. You know,

449
00:29:14,280 --> 00:29:18,600
Speaker 1: like at least one hundred times in a corporate environment,

450
00:29:18,720 --> 00:29:21,160
Speaker 1: I've said to the manager of the leader, the boss,

451
00:29:21,240 --> 00:29:25,120
Speaker 1: him or her, what do you think it's like being

452
00:29:25,120 --> 00:29:28,400
Speaker 1: around you? And ninety nine times out of one hundred

453
00:29:28,480 --> 00:29:32,960
Speaker 1: they say something like fuck, I don't know, or I've

454
00:29:33,000 --> 00:29:37,600
Speaker 1: never thought of that, or oh wow, that's that's And

455
00:29:37,720 --> 00:29:41,240
Speaker 1: I say, look, probably what you think is probably not

456
00:29:41,360 --> 00:29:44,440
Speaker 1: how it is, you know, and that when you think

457
00:29:45,080 --> 00:29:49,440
Speaker 1: that how people experience you, like, for example, on your podcast,

458
00:29:49,480 --> 00:29:52,040
Speaker 1: and your podcast goes great and you go great. But

459
00:29:52,120 --> 00:29:54,360
Speaker 1: let's say, for example, you thought you were doing a

460
00:29:54,400 --> 00:29:59,720
Speaker 1: podcast and oh, this is fucking fascinating, right, but you're

461
00:30:00,000 --> 00:30:03,480
Speaker 1: audience disagree. Guess what all that matters is what they think,

462
00:30:03,520 --> 00:30:07,160
Speaker 1: because they're the fucking listeners. Doesn't matter what you think.

463
00:30:07,680 --> 00:30:10,480
Speaker 1: It matters that you understand what is going to resonate

464
00:30:10,520 --> 00:30:13,320
Speaker 1: with for this, It doesn't matter what you think this example.

465
00:30:13,760 --> 00:30:16,440
Speaker 1: What matters is one how they think, because they decide

466
00:30:16,480 --> 00:30:18,320
Speaker 1: if they're going to come back, same with the you

467
00:30:18,440 --> 00:30:23,480
Speaker 1: project listeners, right, And two your ability. And I'm always

468
00:30:23,520 --> 00:30:25,800
Speaker 1: thinking about this, what do my audience want to hear,

469
00:30:26,040 --> 00:30:28,680
Speaker 1: like to hear, need to hear? And what am I

470
00:30:28,920 --> 00:30:31,680
Speaker 1: like for them? Am I fucking Noel? Do I say

471
00:30:31,720 --> 00:30:32,840
Speaker 1: fuck too much? Tom? I?

472
00:30:32,960 --> 00:30:33,200
Speaker 2: Two?

473
00:30:34,000 --> 00:30:36,720
Speaker 1: Do I need to be tell more stories? Less stories?

474
00:30:36,800 --> 00:30:40,480
Speaker 1: Like I'm trying to understand others and I'm trying to

475
00:30:40,600 --> 00:30:44,400
Speaker 1: understand how they experience me and this show so that

476
00:30:45,200 --> 00:30:49,560
Speaker 1: I can create better connection, better rapport, better trust, better respect,

477
00:30:49,600 --> 00:30:55,200
Speaker 1: better understanding, better congruence so that you know, people want

478
00:30:55,200 --> 00:30:59,760
Speaker 1: to keep learning and evolving. But I'm doing it in

479
00:30:59,800 --> 00:31:04,280
Speaker 1: a way which actually hopefully creates more connection than disconnection.

480
00:31:04,480 --> 00:31:08,440
Speaker 1: So my mission in regards to this is to once

481
00:31:08,480 --> 00:31:12,920
Speaker 1: I'm done, then hopefully go and talk on a bigger

482
00:31:13,000 --> 00:31:17,360
Speaker 1: level and around this idea of understanding how others see us,

483
00:31:18,000 --> 00:31:20,680
Speaker 1: just purely so that we can do all the things

484
00:31:20,760 --> 00:31:25,520
Speaker 1: I said before, better solve problems, work together, understand you know,

485
00:31:25,560 --> 00:31:29,320
Speaker 1: there's so much hatred, right. I'm not saying let's get

486
00:31:29,400 --> 00:31:31,520
Speaker 1: rid of the hatred. I wish we could, but that's

487
00:31:31,560 --> 00:31:36,959
Speaker 1: not practical. What what I'm saying is understand why he

488
00:31:37,040 --> 00:31:40,960
Speaker 1: hates you. That's a good start. Understand why you hate them.

489
00:31:41,280 --> 00:31:44,680
Speaker 1: That's meta cognition, that's you trying to understand you. You know,

490
00:31:44,960 --> 00:31:50,200
Speaker 1: just like I think, better connection, better business, better leadership,

491
00:31:50,240 --> 00:31:56,480
Speaker 1: better management, better efficiency, better productivity is built on greater

492
00:31:56,800 --> 00:32:01,560
Speaker 1: understanding between the various mind in the room, and this

493
00:32:01,720 --> 00:32:02,320
Speaker 1: is part of that.

494
00:32:03,920 --> 00:32:05,520
Speaker 2: And what are the tools for shifting that?

495
00:32:07,160 --> 00:32:10,960
Speaker 1: Well, I think not so much to a tool, but

496
00:32:11,120 --> 00:32:13,920
Speaker 1: like what are the mechanisms, Like what's the thing that

497
00:32:14,000 --> 00:32:18,320
Speaker 1: fucking opens the door? Well, this, this conversation, like this

498
00:32:18,360 --> 00:32:21,240
Speaker 1: is a tool that people Hey, you know, Sally, have

499
00:32:21,320 --> 00:32:23,720
Speaker 1: you ever thought about how other people see you? Or

500
00:32:23,720 --> 00:32:25,760
Speaker 1: perceive you or understand you and why that might matter.

501
00:32:25,840 --> 00:32:28,640
Speaker 1: Listen to Tiff and Craig talk about this. You know,

502
00:32:28,720 --> 00:32:32,480
Speaker 1: if some people might want to share this because what

503
00:32:32,920 --> 00:32:35,400
Speaker 1: I think I could be wrong. Others will disagree, but

504
00:32:35,520 --> 00:32:39,440
Speaker 1: I think this shit's fascinating. And I'm not talking about

505
00:32:39,560 --> 00:32:42,160
Speaker 1: you know, every now and then, some usually Olpha Male goes,

506
00:32:42,200 --> 00:32:44,000
Speaker 1: I don't give a fuck what people think of me.

507
00:32:44,320 --> 00:32:46,840
Speaker 1: I'm just going to fucking be me, and if they

508
00:32:46,840 --> 00:32:49,560
Speaker 1: don't like a day can get I'm like, yeah, well,

509
00:32:49,640 --> 00:32:54,120
Speaker 1: I'm John. How's that going for you at work? Do

510
00:32:54,160 --> 00:32:56,680
Speaker 1: you ever wonder why you've got fucking zero friends and

511
00:32:56,720 --> 00:33:01,400
Speaker 1: why people think you're a douche? Because you know, that's

512
00:33:01,480 --> 00:33:05,560
Speaker 1: not tough, that's not intelligence, that's insecure, and we're not

513
00:33:05,840 --> 00:33:09,800
Speaker 1: you know, if somebody doesn't like me one, that's totally okay.

514
00:33:10,760 --> 00:33:15,440
Speaker 1: Not everybody needs to like me, of course, but I'm

515
00:33:15,520 --> 00:33:19,719
Speaker 1: interested in what that's about. I'm interested in. And if

516
00:33:19,760 --> 00:33:22,080
Speaker 1: somebody just wants to be a hater, I'm not interested.

517
00:33:22,400 --> 00:33:26,920
Speaker 1: But if somebody, you know, it's like early days, maybe

518
00:33:26,960 --> 00:33:29,360
Speaker 1: one hundred episodes into the You Project, a lady sent

519
00:33:29,360 --> 00:33:31,480
Speaker 1: me a message. She went, You're great, love you that

520
00:33:31,480 --> 00:33:35,200
Speaker 1: that are all good. By the way, sometimes you talk

521
00:33:35,240 --> 00:33:37,120
Speaker 1: over the top of your guests. And I went, that's

522
00:33:37,160 --> 00:33:41,920
Speaker 1: a good point, thank you. That's valid. What you're saying

523
00:33:42,200 --> 00:33:46,960
Speaker 1: is critical, but in a good way. It's informed. And

524
00:33:47,480 --> 00:33:49,280
Speaker 1: I went and listened to a bit of stuff. I went,

525
00:33:49,360 --> 00:33:52,440
Speaker 1: she is exactly right. I wrote her an email. I said,

526
00:33:52,440 --> 00:33:55,840
Speaker 1: I listened to a couple of episodes. You're right, thank

527
00:33:55,880 --> 00:34:00,200
Speaker 1: you for the feedback. It's actually valuable, right, because I

528
00:34:00,360 --> 00:34:03,680
Speaker 1: can't be objective about me and you can't be objective

529
00:34:03,680 --> 00:34:07,920
Speaker 1: about you. And while we humans say, oh no, I

530
00:34:08,000 --> 00:34:12,080
Speaker 1: love feedback, no we don't. We fucking hate feedback unless

531
00:34:12,080 --> 00:34:16,960
Speaker 1: it's positive. We don't want critical feedback. We want support,

532
00:34:17,120 --> 00:34:21,120
Speaker 1: we want endorsement. The moment that you give somebody feedback

533
00:34:21,160 --> 00:34:23,840
Speaker 1: they don't want is the moment they start to resent

534
00:34:23,880 --> 00:34:28,040
Speaker 1: you and shut down to you. Now, I'm not suggesting

535
00:34:28,120 --> 00:34:31,080
Speaker 1: we should just walk up to everyone and give them feedback, right,

536
00:34:31,120 --> 00:34:35,560
Speaker 1: That's not what I'm saying. But when you say to me, Harps,

537
00:34:35,600 --> 00:34:39,440
Speaker 1: how can I be better at corporate speaking? And I go, well,

538
00:34:39,480 --> 00:34:41,879
Speaker 1: here's five things you do. Well, here's one or two

539
00:34:41,920 --> 00:34:44,120
Speaker 1: things I reckon you do? Okay, but you could get

540
00:34:44,160 --> 00:34:47,040
Speaker 1: better at. And here's one thing I think that you're

541
00:34:47,080 --> 00:34:50,279
Speaker 1: not doing well at all. Now you can go, oh,

542
00:34:50,360 --> 00:34:53,480
Speaker 1: let's lean into that one, right, or you can go, yeah,

543
00:34:53,520 --> 00:34:57,239
Speaker 1: tell me about the five though, right, tell me how

544
00:34:57,280 --> 00:34:59,200
Speaker 1: good I am at the five Well, you don't need that,

545
00:34:59,280 --> 00:35:01,839
Speaker 1: because you're good the one or two things that are

546
00:35:01,880 --> 00:35:05,400
Speaker 1: okay but could improve. Yep, I would be interested, But

547
00:35:05,480 --> 00:35:07,920
Speaker 1: I personally, tell me about the thing that I'm shit at.

548
00:35:07,960 --> 00:35:09,440
Speaker 1: Why do you think I'm shit at it? What do

549
00:35:09,520 --> 00:35:13,040
Speaker 1: I do? And in your opinion, how might I shift that?

550
00:35:13,719 --> 00:35:19,240
Speaker 1: Because that's like, if you are truly interested in growth

551
00:35:19,320 --> 00:35:23,400
Speaker 1: and personal development and self help, and if these podcasts

552
00:35:23,480 --> 00:35:27,440
Speaker 1: and conversations are really about that and you that is

553
00:35:27,600 --> 00:35:31,960
Speaker 1: genuinely your mission, then you need to be able to

554
00:35:32,200 --> 00:35:35,200
Speaker 1: somehow put your ego and your poor self esteem and

555
00:35:35,239 --> 00:35:39,319
Speaker 1: your insecurity and your fear to one side. Doesn't mean

556
00:35:39,360 --> 00:35:43,400
Speaker 1: it'll vanish and hear what you need to hear versus

557
00:35:43,440 --> 00:35:48,799
Speaker 1: what you're comfortable to hear, you know, because it's I mean,

558
00:35:49,840 --> 00:35:52,600
Speaker 1: why do you think so few people? And I'm not

559
00:35:52,680 --> 00:35:55,399
Speaker 1: throwing my listeners under the bus because I constantly get

560
00:35:55,440 --> 00:35:59,360
Speaker 1: emails and feedback from people who are applying things. But

561
00:35:59,520 --> 00:36:02,760
Speaker 1: broadly speaking, in the world of self help, personal development,

562
00:36:02,800 --> 00:36:07,120
Speaker 1: behavioral psychology, how many people hear things that are relevant

563
00:36:07,160 --> 00:36:11,520
Speaker 1: and potentially helpful and operationalizable or you know, could be

564
00:36:11,560 --> 00:36:14,719
Speaker 1: put into practice but don't do it. I would say

565
00:36:14,760 --> 00:36:19,839
Speaker 1: the vast majority how many people hear something that if

566
00:36:19,880 --> 00:36:23,080
Speaker 1: they put that something into practice would create some kind

567
00:36:23,120 --> 00:36:26,879
Speaker 1: of shift pretty quickly. But just go nah, because I'm

568
00:36:26,920 --> 00:36:29,880
Speaker 1: busy and my ankle saw and you don't understand my situation,

569
00:36:30,040 --> 00:36:33,200
Speaker 1: and you know whatever. And I'm not saying those things

570
00:36:33,239 --> 00:36:35,920
Speaker 1: are not real. But if we want to find a

571
00:36:36,040 --> 00:36:39,880
Speaker 1: reason to be a victim or finder, and I'm not

572
00:36:39,920 --> 00:36:42,160
Speaker 1: saying there are not real victims, of course there are.

573
00:36:42,719 --> 00:36:44,879
Speaker 1: But if we want to find a reason to put

574
00:36:44,920 --> 00:36:47,200
Speaker 1: off the thing we shouldn't put off, we'll find it.

575
00:36:48,320 --> 00:36:52,479
Speaker 2: That's yeah, And that's what was my question came from

576
00:36:52,560 --> 00:36:57,080
Speaker 2: about what then, what people do with it? Once I've

577
00:36:57,080 --> 00:36:59,680
Speaker 2: heard this conversation, where's the practice? Because it's just like

578
00:36:59,719 --> 00:37:03,080
Speaker 2: you said, people can get knowledge about something, so it's

579
00:37:03,120 --> 00:37:06,279
Speaker 2: one thing to go, oh, yeah, I've never thought about that,

580
00:37:06,400 --> 00:37:08,200
Speaker 2: and then you wake up tomorrow and you never think

581
00:37:08,200 --> 00:37:12,440
Speaker 2: about it again. You know, what are the it interests me?

582
00:37:12,520 --> 00:37:15,279
Speaker 2: What the what the tools are, and then when you

583
00:37:15,360 --> 00:37:18,040
Speaker 2: start to open that door, what are all the other

584
00:37:18,200 --> 00:37:20,600
Speaker 2: you know, like how it's very self focused? Oh how

585
00:37:20,600 --> 00:37:23,560
Speaker 2: do people understand me? So I start reading that and

586
00:37:23,560 --> 00:37:26,200
Speaker 2: thinking about it and applying stuff. But what if I

587
00:37:26,239 --> 00:37:29,360
Speaker 2: get to insulin? Forget that? Now I'm not giving a

588
00:37:29,400 --> 00:37:34,240
Speaker 2: fuck about any interest in developing curiosity around who's that person,

589
00:37:34,360 --> 00:37:38,360
Speaker 2: which drives a lot of that behavior and connection and

590
00:37:38,480 --> 00:37:42,279
Speaker 2: interaction as well. So I reckon. That's like I reckon,

591
00:37:42,320 --> 00:37:47,120
Speaker 2: there's so many things that start interweaving peace well.

592
00:37:47,160 --> 00:37:50,480
Speaker 1: And I think also we don't want to be preoccupied

593
00:37:50,640 --> 00:37:53,520
Speaker 1: with what people are thinking of us, right, because then

594
00:37:53,560 --> 00:37:57,400
Speaker 1: you're not going to be yourself right, but just aware

595
00:37:57,960 --> 00:38:01,879
Speaker 1: and you know, like I personally, over the last few

596
00:38:02,000 --> 00:38:06,760
Speaker 1: years have been I don't often say this but much.

597
00:38:07,160 --> 00:38:09,000
Speaker 1: I don't know if I've been braver, but I feel

598
00:38:09,040 --> 00:38:12,400
Speaker 1: like not that I don't care what people think of me.

599
00:38:12,520 --> 00:38:14,239
Speaker 1: If I said that, that would be a lie. Of

600
00:38:14,280 --> 00:38:16,759
Speaker 1: course I care what people think of me. I'm human, right,

601
00:38:17,400 --> 00:38:19,919
Speaker 1: but I don't care as much. I care that I'm

602
00:38:19,920 --> 00:38:26,960
Speaker 1: being authentic, and I care that that I'm I'm as

603
00:38:27,120 --> 00:38:32,799
Speaker 1: close to you know, public me, personal me, private me, secret, me,

604
00:38:32,880 --> 00:38:35,680
Speaker 1: you know, those four layers of the me. You know,

605
00:38:35,760 --> 00:38:39,040
Speaker 1: and what most people give on a podcast is public me.

606
00:38:39,800 --> 00:38:43,160
Speaker 1: It's that public gnatif how you being Oh yeah, what

607
00:38:43,200 --> 00:38:46,160
Speaker 1: do you do over? But that's the kind of public

608
00:38:46,560 --> 00:38:49,919
Speaker 1: that's the persona, that's the I'm on a microphone, we're

609
00:38:49,960 --> 00:38:53,280
Speaker 1: having a chat, and there's it's not that it's bullshit,

610
00:38:53,360 --> 00:38:55,680
Speaker 1: but there's a lot that you're not really getting. And

611
00:38:55,719 --> 00:38:59,560
Speaker 1: for me, it's more I want to be almost that

612
00:39:00,239 --> 00:39:03,680
Speaker 1: private me, the one that generally only a few people

613
00:39:03,719 --> 00:39:07,720
Speaker 1: get access to. Like personal you, that's who your friends

614
00:39:07,719 --> 00:39:12,480
Speaker 1: and family see. Private you is the person that maybe

615
00:39:12,520 --> 00:39:15,520
Speaker 1: a few very close people to you or one know.

616
00:39:16,200 --> 00:39:18,640
Speaker 1: And then secret you is the you that only you know.

617
00:39:19,640 --> 00:39:22,120
Speaker 1: For me, and I don't always do it, but I

618
00:39:22,320 --> 00:39:27,360
Speaker 1: want to. There's and of course there's stuff for personal

619
00:39:27,400 --> 00:39:29,480
Speaker 1: reasons that I wouldn't share with the world, but nothing

620
00:39:30,400 --> 00:39:35,000
Speaker 1: nothing controversial law, but it's just wouldn't help people, you know,

621
00:39:35,040 --> 00:39:37,960
Speaker 1: it's not relevant. But all the stuff about me that

622
00:39:38,120 --> 00:39:42,399
Speaker 1: like my insecurity, my bullshit, my you know. By the way,

623
00:39:42,480 --> 00:39:44,719
Speaker 1: I'm like, I don't pretend I'm a great academic. I

624
00:39:44,760 --> 00:39:48,560
Speaker 1: tell people I'm not because I want to encourage people, Look,

625
00:39:48,640 --> 00:39:51,200
Speaker 1: if I can do this, not necessarily you can, but

626
00:39:51,480 --> 00:39:53,880
Speaker 1: there's a fair chance you can. And if I can

627
00:39:53,960 --> 00:39:56,680
Speaker 1: get a PhD when I'm sixty one, what can you do?

628
00:39:57,000 --> 00:40:00,000
Speaker 1: And if I can have average genetics and figure out

629
00:40:00,120 --> 00:40:03,680
Speaker 1: a way to optimize my genetics, so can you. And

630
00:40:03,760 --> 00:40:06,000
Speaker 1: if I went to school in the country where we

631
00:40:06,080 --> 00:40:10,040
Speaker 1: didn't even talk about careers or like there was that

632
00:40:10,160 --> 00:40:13,480
Speaker 1: wasn't even a conversation, guidance, counseling going, and it wasn't

633
00:40:13,480 --> 00:40:15,520
Speaker 1: even a thought. You just go get a job, and

634
00:40:15,560 --> 00:40:18,919
Speaker 1: you probably just got the job that you had access to, right.

635
00:40:20,080 --> 00:40:23,120
Speaker 1: And if I can be in you know, relationships that

636
00:40:23,160 --> 00:40:26,320
Speaker 1: are good and bad, and I can start a business

637
00:40:26,320 --> 00:40:30,120
Speaker 1: from scratch not knowing what I'm doing in an industry

638
00:40:30,120 --> 00:40:33,239
Speaker 1: that doesn't exist, a profession that doesn't exist without any

639
00:40:33,280 --> 00:40:37,279
Speaker 1: regulation or insurance, personal training, and then figure out how

640
00:40:37,320 --> 00:40:41,240
Speaker 1: to build a business out of something that didn't exist

641
00:40:41,360 --> 00:40:47,279
Speaker 1: with minimal fucking business skills, commercial understanding, leadership skills. Then

642
00:40:47,360 --> 00:40:50,279
Speaker 1: and I did that, then you go, oh, sure, I'm

643
00:40:50,320 --> 00:40:52,759
Speaker 1: not a genius, but I can. If I can work

644
00:40:52,800 --> 00:40:56,319
Speaker 1: hard enough and long enough and be brave enough, I

645
00:40:56,360 --> 00:41:01,440
Speaker 1: can do some cool shit but also soak and everyone,

646
00:41:01,840 --> 00:41:03,839
Speaker 1: you know. So for me, it's that I don't know

647
00:41:03,840 --> 00:41:07,279
Speaker 1: how we got there, but that I just think that

648
00:41:07,640 --> 00:41:11,960
Speaker 1: this whole kind of you know, this this nuanced layer

649
00:41:12,040 --> 00:41:17,600
Speaker 1: of awareness and communication and people stuff, it's just another

650
00:41:17,800 --> 00:41:20,800
Speaker 1: kind of piece in the jigsaw puzzle that is human

651
00:41:20,840 --> 00:41:22,360
Speaker 1: behavior and human connection.

652
00:41:23,600 --> 00:41:25,480
Speaker 2: What are you going to do when you get the

653
00:41:25,480 --> 00:41:28,319
Speaker 2: little little hat, little PhD hat on your head. You're

654
00:41:28,320 --> 00:41:29,960
Speaker 2: going to have a celebration and you and have some

655
00:41:30,080 --> 00:41:31,799
Speaker 2: time off. You're going to roll around on the floor

656
00:41:31,840 --> 00:41:32,359
Speaker 2: with your dog.

657
00:41:33,200 --> 00:41:35,279
Speaker 1: Yeah, I'm going to get a dog. I'm going to

658
00:41:35,280 --> 00:41:39,319
Speaker 1: get a dog. I'm going to get my PhD in

659
00:41:39,360 --> 00:41:41,800
Speaker 1: a frock with no jocks on and not tell anyone.

660
00:41:41,920 --> 00:41:44,560
Speaker 1: I'm just going to know. I'm just I'm just going

661
00:41:44,640 --> 00:41:47,160
Speaker 1: to be up there free balling. The world won't know.

662
00:41:47,920 --> 00:41:52,239
Speaker 1: Outside it's going to be all business and academia underneath,

663
00:41:52,840 --> 00:41:56,520
Speaker 1: just you know, party. I'll probably get a dog. I

664
00:41:56,560 --> 00:41:58,399
Speaker 1: want to get a dog when i'm because I can't

665
00:41:58,640 --> 00:42:01,480
Speaker 1: look after right now, because I'd have to ignore the

666
00:42:01,520 --> 00:42:03,839
Speaker 1: dog half the day. And so I want to get

667
00:42:03,840 --> 00:42:06,120
Speaker 1: a dog and train the dog and walk the dog

668
00:42:06,200 --> 00:42:10,040
Speaker 1: and invest the appropriate amount of time and energy, especially

669
00:42:10,040 --> 00:42:12,840
Speaker 1: in the first six months to bond with the dog

670
00:42:13,440 --> 00:42:17,000
Speaker 1: and train the dog the way that you know. Of course,

671
00:42:17,040 --> 00:42:19,200
Speaker 1: I want a high performance weapon of a dog, not

672
00:42:19,280 --> 00:42:22,240
Speaker 1: that fucking thing that you've got that just licks and eats.

673
00:42:23,680 --> 00:42:28,400
Speaker 2: I'll parden. She's a weapon, and she's got great shoes.

674
00:42:28,760 --> 00:42:32,760
Speaker 1: I see. This is the problem with you fucking dog parents.

675
00:42:32,840 --> 00:42:37,160
Speaker 1: That ANTHROPOMORPHI is your animals. No dog dog dogs are dogs,

676
00:42:37,160 --> 00:42:38,040
Speaker 1: They're not people.

677
00:42:38,239 --> 00:42:40,879
Speaker 2: She has to wear shoes otherwise she gets She had

678
00:42:40,880 --> 00:42:43,160
Speaker 2: surgery last year to get the grit removed. It's a

679
00:42:43,239 --> 00:42:48,799
Speaker 2: necessity now and it's very cute. I'm going to bring

680
00:42:48,840 --> 00:42:50,920
Speaker 2: her to Hampton one day for a walk so that

681
00:42:50,960 --> 00:42:53,160
Speaker 2: you can hear a cop clopping on the pavement and

682
00:42:53,200 --> 00:42:55,920
Speaker 2: you will just melt. You'll have a whippet in noeime.

683
00:42:56,040 --> 00:42:58,080
Speaker 2: I sent you a whippet that you could adopt today.

684
00:42:58,440 --> 00:42:59,799
Speaker 2: I thought it might be on your way to pick

685
00:42:59,840 --> 00:43:01,840
Speaker 2: it up already. To be honest, he was a.

686
00:43:01,840 --> 00:43:02,600
Speaker 1: Four year old boy.

687
00:43:02,600 --> 00:43:04,640
Speaker 2: I don't know that we were seven months.

688
00:43:05,200 --> 00:43:08,440
Speaker 1: I thought he was four years old. Maybe there was

689
00:43:08,480 --> 00:43:11,360
Speaker 1: four photos. Yes, anyway, let's.

690
00:43:11,120 --> 00:43:14,400
Speaker 2: Not it was relevant somehow.

691
00:43:17,239 --> 00:43:19,360
Speaker 1: I'm going to give a quick plug because that's just

692
00:43:19,440 --> 00:43:23,839
Speaker 1: how I roll Feb. Three, I'm starting my mentoring program, which,

693
00:43:23,880 --> 00:43:28,920
Speaker 1: as we record, is next Monday. It's next Monday. If

694
00:43:28,920 --> 00:43:31,520
Speaker 1: you want to think about that or learn more about that,

695
00:43:31,560 --> 00:43:33,400
Speaker 1: go to my website, Craig Carpa dot in the just

696
00:43:33,400 --> 00:43:36,919
Speaker 1: go the education section, click on that and you find

697
00:43:36,920 --> 00:43:40,560
Speaker 1: out all about it. Cookie, it's been great.

698
00:43:41,080 --> 00:43:41,880
Speaker 2: Thanks Harps.

699
00:43:42,040 --> 00:43:46,239
Speaker 1: Pleasure always I feel like talking about over talking. I

700
00:43:46,320 --> 00:43:47,480
Speaker 1: definitely over talked.

701
00:43:48,040 --> 00:43:49,920
Speaker 2: I was in the classroom this time.

702
00:43:50,040 --> 00:43:54,080
Speaker 1: Or maybe with thank you to know what topic? Yeah,

703
00:43:54,280 --> 00:43:56,879
Speaker 1: well say goodbye affair as always, but for now, thank you.

704
00:43:57,080 --> 00:43:57,760
Speaker 1: Thanks everyone,