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Speaker 1: Well, today's a holiday that we don't really acknowledge. I'll

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Speaker 1: just say happy hang out with your family and friends day.

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Speaker 2: And tomorrow is the most American of holidays. This is

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Speaker 2: a celebration of consumerism, yes, aka Black Friday. But some

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Speaker 2: of y'all are going to be in for quite the surprise.

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Speaker 2: Do you know just how many packages are going to

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Speaker 2: be in the mix with everybody ordering stuff online?

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Speaker 1: I don't even want to try and conceptualize it because

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Speaker 1: I know that I can't because Black Friday, when we

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Speaker 1: were younger, it was just, you know, one day there

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Speaker 1: was all these sales.

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Speaker 3: Now it extends.

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Speaker 1: Where it's like you got Black Friday, but the Black

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Speaker 1: Friday deals start on Wednesday and Cyber Monday. There's Cyber Monday.

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Speaker 1: So it's really a full calendar week of hurry.

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Speaker 3: Up and buy all this stuff.

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Speaker 2: But the real gag is if you didn't place your

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Speaker 2: order in July, it won't be here by Christmas. We'll

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Speaker 2: tell you why.

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Speaker 1: The whole shipping from purchasing to getting the product at

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Speaker 1: your door is a very complex system that I feel.

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Speaker 3: Like none of us know much about.

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Speaker 2: I know, I don't understand how I'm placing an order

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Speaker 2: and it's here within sixteen hours.

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Speaker 1: Honestly, And I feel like as technology advances, and some

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Speaker 1: of this technology that we know nothing about advances, we're

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Speaker 1: expecting things to show up sooner and sooner and sooner.

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Speaker 1: But with every great thing, you know that there's some

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Speaker 1: not so great things happening behind the scenes.

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Speaker 2: Yes, the dark side of shipping.

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Speaker 1: Yes, I'm TT and I'm Zachiah and from Spotify. This

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Speaker 1: is Dope Labs. Welcome to Dope Labs, a weekly podcast

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Speaker 1: that mixes hardcore science, pop culture, and a healthy dose

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Speaker 1: of friendship.

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Speaker 2: This week, we're diving into the world of commerce, supply chains,

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Speaker 2: and transportation. Specifically, we want to know how a product

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Speaker 2: goes from click to ship, away from the factory and

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Speaker 2: to your front door.

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Speaker 1: All right, let's get into the recitation. What do we know, TT, Well,

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Speaker 1: we know that shipping is usually really really fast, and

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Speaker 1: there have been some shipping delays.

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Speaker 2: There's so many industries involved in getting products to your door, manufacturing, routing, weather, economics,

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Speaker 2: and today we're focusing on shipping more specifically, how issues

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Speaker 2: in the trucking industry are affecting shipping logistics and the

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Speaker 2: shipping delays don't make sense to me. It's specific things

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Speaker 2: missing from the grocery store. There's no bug spray like

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Speaker 2: the chemical killer bug spray, only essential old buck spray

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Speaker 2: at my grocery store.

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Speaker 3: That's not good enough for my friend. Let me tell you.

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Speaker 2: Lemon grass everywhere, okay, citronella everywhere.

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Speaker 1: Anybody's citronella. And I'm like, that does not work for me.

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Speaker 1: And the sindos will come. And what we also know

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Speaker 1: is that demand for delivery is increasing across the board,

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Speaker 1: like delivery of the past, where it's just like, oh,

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Speaker 1: you know, you might get a TV delivered, you might

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Speaker 1: get a computer delivered. Now we're like, okay, I need

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Speaker 1: my vitamins delivered, I need my groceries delivered. Everything is

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Speaker 1: being delivered at this point, and I feel like that

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Speaker 1: was enhanced because we were all working from home or

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Speaker 1: staying at home because of the pandemic.

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Speaker 2: Also, that demand for delivery and shipping things across this

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Speaker 2: country has been exacerbated by the trucker shortage. You know,

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Speaker 2: I saw some signs. I don't know if it was

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Speaker 2: a bad sheet or whatever. I was going down eighty

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Speaker 2: five and it said trucker strike and it had a date,

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Speaker 2: and I said I don't want to cross the line.

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Speaker 2: I don't even know what it means, because I mean,

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Speaker 2: I don't drive on the highway too with them. I mean,

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Speaker 2: I want to know what's going on. I've been seeing

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Speaker 2: this happen in the.

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Speaker 1: UK, but it's also happening here too, Right, we did

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Speaker 1: see that the UK was having petro shortages and other

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Speaker 1: things that. So there's something happening that we don't understand. Yes,

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Speaker 1: so what do we want to know considering all that stuff.

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Speaker 1: I know it's somehow tied together, but how what are

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Speaker 1: the specifics? And I want to understand the trucker shortage.

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Speaker 1: I didn't even know what was going on. My friend

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Speaker 1: should be hitting the road and so she told me

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Speaker 1: what she saw, and I had no idea what is

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Speaker 1: going on with this trucker shortage?

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Speaker 2: And then how does the gig economy play into this?

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Speaker 2: You know, now you can send a package across town

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Speaker 2: with Uber and also just the use of all these

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Speaker 2: like subcontracting services to get things from point A to

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Speaker 2: point B. How does that work into the big picture

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Speaker 2: of shipping?

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Speaker 1: Yeah, and then for me, I want to know what

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Speaker 1: we can do as consumers to like alleviate or to

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Speaker 1: get rid of some of the problems that are cropping

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Speaker 1: up because of this increased shipping world that we're in.

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Speaker 2: Let's jump into the dissection.

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Speaker 3: Dissect Sean dissect Sean. Our guest for today's lab is

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Speaker 3: Christopher Mems.

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Speaker 4: My name is Christopher Mems, and I am a technology

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Speaker 4: columnist at the Wall Street Journal.

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Speaker 2: Christopher is talking to us about his new book Arriving Today,

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Speaker 2: which is about how products get from the factory to

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Speaker 2: our front door. So first we wanted to know how

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Speaker 2: and where things are produced before they're sold. We know

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Speaker 2: that most things we buy today are not produced in

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Speaker 2: the US, and that's.

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Speaker 3: Because of globalization.

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Speaker 1: Globalization allows people to buy goods cheaply from all over

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Speaker 1: the world.

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Speaker 3: But how is this possible logistically?

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Speaker 2: According to Christopher, we can trace the history of globalization

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Speaker 2: back to the shipping container and the Vietnam War.

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Speaker 4: What happened during the Vietnam War was the American military

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Speaker 4: machine needed so much material that they needed a new

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Speaker 4: way to move goods into the country.

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Speaker 1: And this is where American businessman Malcolm MacLean steps in,

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Speaker 1: who since the nineteen fifties had been developing the world's

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Speaker 1: first modern shipping container.

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Speaker 2: And the shipping container is really critical. It's this intermodal

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Speaker 2: part of globalization that means it's going from a ship

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Speaker 2: to a truck to a train, and so those dimensions

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Speaker 2: have to be the same in every place, basically making

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Speaker 2: it universal.

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Speaker 4: The shipping contator was a classic chicken and egg problem

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Speaker 4: because you needed everybody to agree on the dimensions and

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Speaker 4: the specifications for a shipping container so that all the

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Speaker 4: ships could carry all the shipping containers, and also the

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Speaker 4: trains could accommodate them and trucks.

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Speaker 3: So how big are these shipping containers?

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Speaker 2: Well, ISO, which is the International Organization for Standardization, has

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Speaker 2: determined that a standard container is eight feet wide about

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Speaker 2: eight and a half feet high, and then they can

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Speaker 2: either be twenty feet long or forty feet long. So

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Speaker 2: big big, And so when you think about that, I

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Speaker 2: don't know about you, but once we started moving into

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Speaker 2: cubic feet, I'm out of there.

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Speaker 3: Right.

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Speaker 1: I had you at eight feet wide, Okay, I had

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Speaker 1: you at eight feet tall, but then twenty feet I

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Speaker 1: was like a right.

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Speaker 2: So if you think about a twenty foot container, m hmm,

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Speaker 2: that's enough room for almost one hundred washing machines or so,

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Speaker 2: and some of these containers can be refrigerated or insulated.

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Speaker 2: Some of them have an open top. You ever see

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Speaker 2: those trains that have the shipping containers on them and

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Speaker 2: you can see the stuff on the top.

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Speaker 3: Mm hmm.

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Speaker 2: Isn't that stuff gonna blow out? Don't they need to

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Speaker 2: cover over there?

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Speaker 3: I guess they've thought about what to do.

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Speaker 4: And so the American military saw this idea and said,

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Speaker 4: all right, we're gonna break the log jam. Malcolm McLean,

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Speaker 4: we like your idea, we like your specifications, and they

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Speaker 4: created such a large demand on their own.

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Speaker 1: The demand for shipping containers was so high from the

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Speaker 1: Department of Defense that Malcolm McLean's design became the international standard.

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Speaker 4: And very soon after you had bigger and bigger ships

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Speaker 4: to carry all of these shipping containers, and that meant

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Speaker 4: bigger cranes and ports to accommodate them. And it was

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Speaker 4: just billions and billions of dollars of investment, and that

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Speaker 4: created the global infrastructure which allowed globalization to happen and

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Speaker 4: is the reason that we can buy goods from everywhere.

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Speaker 2: So basically, the shipping container was a game changer.

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Speaker 1: Once the shipping container arrived, this basically made it so

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Speaker 1: that the idea of really having a global economy was

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Speaker 1: right in front of us, like it became possible, and

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Speaker 1: there was a need for a whole new level of

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Speaker 1: worker productivity. And that's when we get into scientific management.

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Speaker 2: So what is scientific management?

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Speaker 4: Any place you have software or an algorithm that can

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Speaker 4: watch how people work and then dictate to them the

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Speaker 4: pace and the manner of that work. That's scientific management,

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Speaker 4: even though we don't call it by that name.

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Speaker 1: The concept of scientific management was invented by Frederick Taylor,

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Speaker 1: and he published a book that was titled The Principles

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Speaker 1: of Scientific Management in nineteen oh nine. And it was

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Speaker 1: around this time that Henry Ford, you know like the car,

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Speaker 1: invented the assembly line, which reduced the time it took

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Speaker 1: to build an automobile from twelve hours to one hour

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Speaker 1: and thirty three minutes.

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Speaker 2: That's crazy gains.

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Speaker 4: It was just this notion that if you could measure

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Speaker 4: the amount of time that it took for a worker

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Speaker 4: to complete every single action, if they were working in

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Speaker 4: a factory, which remember we're still kind of new at

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Speaker 4: the time, or if they were working on an assembly line,

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Speaker 4: which at the time was brand new, then you could

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Speaker 4: use these techniques to manage people scientifically and speed up work.

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Speaker 2: So in order to employ scientific management, you really need

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Speaker 2: some method of surveillance or tracking. And before the age

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Speaker 2: of digital surveillance, there were stop watches.

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Speaker 1: So what Frederick Taylor was doing was that he would

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Speaker 1: go into a factory, you say, who's the best worker here,

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Speaker 1: and they would point to that person, and then he

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Speaker 1: would say, work as hard as you can, and I'm

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Speaker 1: going to time you using this stopwatch. And then he

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Speaker 1: was able to determine the productivity of the most productive person,

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Speaker 1: and based off of that information, they were able to

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Speaker 1: simplify and optimize jobs so that workers could be as

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Speaker 1: productive as possible.

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Speaker 2: This doesn't really sound like a fulfilling or satisfying work environment.

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Speaker 3: Now, this sounds awful.

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Speaker 4: It ended up being this way that workers were pushed

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Speaker 4: to their limits and beyond. Of course, the irony is

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Speaker 4: that scientific management is how work, especially work in factories

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Speaker 4: and warehouses and ports many other places call centers fast food.

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Speaker 4: This is how all of work is organized.

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Speaker 3: That's so true.

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Speaker 1: I think a lot of us can think about our

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Speaker 1: jobs and listening to what scientific management is, see how

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Speaker 1: some of those things are in all of our workspaces,

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Speaker 1: and scientific management isn't only happening in the workplace now.

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Speaker 1: There's a lot of tools that can be used to

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Speaker 1: monitor employees' productivity when they're working from home, which a

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Speaker 1: lot of us are right now.

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Speaker 4: With the advent of remote work, more and more companies

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Speaker 4: are surveilling their employees when they're working at home right

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Speaker 4: because they don't have FaceTime. You know, managers can't manage

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Speaker 4: by walking around anymore. Companies will give you a company

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Speaker 4: issue laptop or mobile device, and then they're watching the

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Speaker 4: hours that you're actually doing your work.

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Speaker 2: This reminds me of that TikTok where the girl has

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Speaker 2: a fan and it's like an oscillating fan and it's

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Speaker 2: to something and it's moving the mouse around, so it

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Speaker 2: seems like she's working genius.

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Speaker 3: Genius. She was like, scientific management, I'll.

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Speaker 2: Do I'll manage you. But you know what's also really interesting,

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Speaker 2: it's not always the manager imposing this type of system

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Speaker 2: on the workers. Sometimes workers elect to use different productivity

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Speaker 2: tools to help improve their own output and their own focus.

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Speaker 2: I know, I do, so do I I use one note,

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Speaker 2: we use airtable slack.

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Speaker 3: Lots of folks are using slack.

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Speaker 1: All types of stuff I used to use ASNA to

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Speaker 1: improve our productivity or make us more efficient, work faster,

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Speaker 1: get more done in a shorter amount of time. So

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Speaker 1: we are enforcing these scientific management concepts on ourselves.

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Speaker 2: Staff punking ourselves right on into the nine to five.

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Speaker 2: So these tools can be good. You know, we use

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Speaker 2: airtable that helps us stay on track with our episodes,

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Speaker 2: know what's happening. It also can help us move projects forward.

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Speaker 2: We can collaborate better with our team.

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Speaker 1: But that said, all of that can be a slippery

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Speaker 1: slope and we're going to get into that right after

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Speaker 1: the break.

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Speaker 2: All right, we're back.

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Speaker 1: Yes, And as we're talking about all of the shipping

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Speaker 1: and everything like that, it really makes me think about

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Speaker 1: how we're going to be purchasing. Everybody's going to be

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Speaker 1: online shopping from their phones mostly. I think I think

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Speaker 1: everybody shops on their phones these days.

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Speaker 2: And watching the notifications from my banking.

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Speaker 3: Gap saying girl, what is you doing?

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Speaker 2: Dot do transaction.

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Speaker 1: But there's so many apps out there, and our next

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Speaker 1: lab is going to be all about fintech. So these

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Speaker 1: are apps that help you organize your finances and get

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Speaker 1: financially healthy.

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Speaker 2: Yes, and I'm excited about it because our guest is

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Speaker 2: Natalia Razinski, the head of strategy at Klarna. Oh yes,

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Speaker 2: this is the perfect person to talk to about helping us.

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Speaker 2: All right, let's get back to today's lab. We're talking

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Speaker 2: to Wall Street Journal reporter Christopher Mims about his new book,

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Speaker 2: arriving today.

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Speaker 1: In the first half of the dissection, we focus mostly

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Speaker 1: on how goods and products are being made using tools

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Speaker 1: like scientific management to produce things efficiently for the global market.

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Speaker 2: But Christopher's book also focuses on the transport of those items.

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Speaker 2: And before you even click add tokar, that product has

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Speaker 2: already been on a very long journey, a journey that

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Speaker 2: starts at the factory.

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Speaker 4: Generally, the way a lot of finished goods, and especially

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Speaker 4: consumer electronics get to us is you know, they are

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Speaker 4: first made increasingly in Southeast Asia. A lot of things

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Speaker 4: we think are made in China are actually made Thailand, Vietnam, Malaysia,

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Speaker 4: places like that.

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Speaker 1: From the factory, it goes to a small port, put

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Speaker 1: into a shipping container.

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Speaker 2: Shout out to Malcolm maclain.

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Speaker 1: Then the shipping container gets put onto a barge where

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Speaker 1: it gets taken to a much larger.

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Speaker 4: Port where it stays for a couple of days after

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Speaker 4: being lifted off by a giant crane. Then that big

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Speaker 4: crane puts it onto a really big ship.

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Speaker 2: And we mean big. Some of these cargo ships are

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Speaker 2: as big as the Empire State Building being laid on

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Speaker 2: its side. We're talking the length of three football fields.

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Speaker 2: This is not the boat that Megan thee Stallion was

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Speaker 2: talking about driving.

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Speaker 3: You can't drive that vote.

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Speaker 2: No.

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Speaker 1: Each container ship can hold up to ten thousand forty

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Speaker 1: foot containers or about sixty thousand pounds of goods, and

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Speaker 1: then it.

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Speaker 4: Can travel all the way across the Pacific Ocean, and

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Speaker 4: that's going to take weeks because it's actually moving kind

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Speaker 4: of slow in order to save on fuel.

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Speaker 2: Finally, the ship arrives Stateside, most often at the ports

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Speaker 2: of la and Long Beach, and that's where about forty

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Speaker 2: to fifty percent of all goods from Asia arrive in

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Speaker 2: the US.

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Speaker 4: Then those containers get put onto a truck for the

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Speaker 4: first time, and that's called drayage, and the container gets

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Speaker 4: taken to a warehouse in the Inland Empire.

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Speaker 2: That's a region in southern California.

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Speaker 4: All the goods are emptied out of the container put

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Speaker 4: onto a long haul truck. It might drive halfway across

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Speaker 4: the country. Then all of those cardboard boxes full of

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Speaker 4: goods go into what's known as a fulfillment if you're

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Speaker 4: talking about Amazon, and human beings have to open up

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Speaker 4: every single one of those boxes, take every item out,

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Speaker 4: scan it, put it into a bin. The bin goes

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Speaker 4: onto a conveyor, which goes to another human being which

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Speaker 4: takes all the goods stows it on a robot shelf,

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Speaker 4: which then scoots away like R two D two.

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Speaker 1: Oh my goodness, this is a lot. I am exhausted.

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Speaker 1: And that's just.

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Speaker 3: The first part of the product's journey.

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Speaker 1: Okay, So now that the item is on the shelf

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Speaker 1: waiting for someone to buy it, what happens next?

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Speaker 4: And then when you order that good which has been

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Speaker 4: on a fourteen thousand mile two month minimum journey, when

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Speaker 4: you order it for delivery the next day, within forty

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Speaker 4: five minutes, someone has picked that item off of the

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Speaker 4: robot's shelf, goes into a bin. The bin is carried

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Speaker 4: on a conveyor down to the pack station. A person

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Speaker 4: puts the items in a box, tapes up the box.

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Speaker 4: Box goes down another conveyor into the back of a truck,

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Speaker 4: which goes to another warehouse where it's sorted, and then

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Speaker 4: the final warehouse, which is called the delivery station, where

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Speaker 4: all the boxes get stacked up about like you know,

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Speaker 4: two three in the morning for delivery on a truck

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Speaker 4: to your home the next day, you know it's next

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Speaker 4: day or two day delivery.

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Speaker 2: Most people are not thinking about all of this when

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Speaker 2: they add to cart, especially with things like two day delivery,

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Speaker 2: one click ordering overnight shipping.

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Speaker 1: Yes, I am ordering my goods by the light of

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Speaker 1: the moon. Most likely I'm in my bed and I'm

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Speaker 1: just like click, everything just starts getting ship.

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Speaker 3: I don't even think about it. I just keep swiping.

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Speaker 2: This just also feels like so many steps for me

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Speaker 2: to get the few little things that I'm adding to cart.

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Speaker 2: This is kind of changing things for.

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Speaker 1: Me, honestly, because you think about every single step and

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Speaker 1: all the ships and shipping containers and cranes and people

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Speaker 1: and trucks. This is a lot for me to be saying, Okay,

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Speaker 1: I just need this new cell phone case that I

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Speaker 1: found on this website that's six ninety nine.

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Speaker 2: That's a lot exactly it. Every time I get ready

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Speaker 2: to order something online, now I'm gonna say, am I

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Speaker 2: ready to turn on the crane to pick up my items,

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Speaker 2: you know, like it might not be worth it.

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Speaker 3: It might not be worth the crane movement.

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Speaker 2: And there's all this automation, but then there's all this

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Speaker 2: on the ground stuff too, And one of them that

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Speaker 2: we really should zero in on is the truck.

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Speaker 1: Even though the trucker shortage has reached crisis levels this

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Speaker 1: year and been on the front page of Labor News,

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Speaker 1: the trucker shortage isn't really new.

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Speaker 2: Trucks are an essential part of the global economy. In

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Speaker 2: the United States, seventy percent of all freight is transported

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Speaker 2: by trucks. And it may feel like a cliche, but

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Speaker 2: America really does run on trucks, not duncan. Yeah you

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Speaker 2: thought it was duncan, but it's actually trucks. So when

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Speaker 2: we don't have enough people to drive those trucks, it

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Speaker 2: can cause some pretty big problems for the economy.

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Speaker 4: It's affecting everything from what appears on stores at the

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Speaker 4: grocery store, to getting school's school lunches, to people talking

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Speaker 4: about why they can't get their couch delivered.

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Speaker 1: And with so many items being shipped to people and

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Speaker 1: they're being a trucker shortage that can lead to trucker

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Speaker 1: burnout for the truckers that are now left to carry

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Speaker 1: the load. We wanted to know what's really driving this shortage.

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Speaker 1: Why don't we have enough truckers to handle the shipping demand.

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Speaker 4: There was this amazing piece in the New York Times

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Speaker 4: in twenty seventeen, and there was this heartbreaking quote in

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Speaker 4: it where this trucker said, you know, we feel like

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Speaker 4: throw away people. There's all these small injustices in the industry,

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Speaker 4: which the net effect is that, you know, there's about

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Speaker 4: three and a half million truckers in America, there's ten

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Speaker 4: million people who have a commercial driver's license. Those are

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Speaker 4: all the people who went into the industry and burned

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Speaker 4: out and are just like, I'm not going to be

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Speaker 4: a truck driver anymore.

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Speaker 2: Those numbers are staggering, honestly, and it makes sense when

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Speaker 2: you understand the experiences that a lot of truckers have.

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Speaker 4: The challenge in trucking is that even as rates go

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Speaker 4: up and wages go up, the quality of life is low.

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Speaker 4: So the average truck driver is on the road twenty

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Speaker 4: one days out of every month. They're working fourteen hours

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Speaker 4: a day.

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Speaker 1: Let me tell you something I can't do anything for

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Speaker 1: that long and that many consecutive days, maybe sleep, maybe sleep,

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Speaker 1: and even then, you know, you get tired.

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Speaker 3: You still get tired of sleeping.

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Speaker 1: And so I can't imagine having to be alert at

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Speaker 1: the wheel of this huge machine that's carrying all these goods.

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Speaker 1: And it's not always like a perfect sunny day out

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Speaker 1: in the rain, in the snow and a hurricane. We're

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Speaker 1: still expecting our packages. So they can't call out, they

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Speaker 1: can't say, oh no, there's a storm, I'm not coming.

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Speaker 1: They have to hit the road. And when you really

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Speaker 1: look at it, there's also the issue of stagnating wages.

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Speaker 1: So if you look at what the average trucker made

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Speaker 1: in the United States in around the eighties, it was

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Speaker 1: about thirty six thousand dollars a year, and in twenty

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Speaker 1: twenty bucks that's about one hundred and twenty thousand dollars.

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Speaker 1: But by twenty nineteen the average wage was only forty

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Speaker 1: five thousand dollars. So when you normalize all that out

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Speaker 1: for like inflation and all that, what you're looking at

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Speaker 1: is actually a sixty three percent decrease in wages over

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Speaker 1: a forty year time period. Christopher explained that sometimes big

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Speaker 1: trucking companies will cover the upfront costs for a commercial

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Speaker 1: driver's license or a CDL, which could be seven thousand

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Speaker 1: dollars or more, but that has to be paid back.

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Speaker 4: So they got to work like a year just to

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Speaker 4: pay that off. They're getting paid by the mile, and

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Speaker 4: when you're a trucker and you stop at a warehouse,

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Speaker 4: you're not getting paid for that time.

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Speaker 2: That's a lot of unpaid labor. So what we're seeing

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Speaker 2: is the cost of shipping going down while the cost

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Speaker 2: of living has only gone up.

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Speaker 1: Okay, so only getting paid by the mail or during

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Speaker 1: quote unquote productive time sounds like scientific management to me.

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Speaker 1: And this really doesn't take into account that people like

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Speaker 1: machines need maintenance.

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Speaker 3: People have to go to the.

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Speaker 1: Bathroom, they have to shower, they have to eat, and

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Speaker 1: they have to sleep and that's just basic survival. So

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Speaker 1: it's no wonder that all these truckers are burning out

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Speaker 1: and choosing to have other.

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Speaker 3: Types of jobs.

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Speaker 2: Yeah, it feels like all of this is also coming

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Speaker 2: to a head during the pandemic, and so you have

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Speaker 2: to kind of ask why, now, how do we get

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Speaker 2: to this place where the trucking industry has become unsustainable

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Speaker 2: for the folks who are driving it, for the truckers.

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Speaker 4: At the beginning of the pandemic, all the companies thought

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Speaker 4: this is gonna be like the Great Recession. Demand's gonna

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Speaker 4: go down. So they're like, Okay, I'm going to book

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Speaker 4: fewer shipping containers, less trucks, I'm gonna buy less stuff.

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Speaker 4: But then the opposite happened. America went shopping and demand

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Speaker 4: is now so much higher for everything than it was before.

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Speaker 3: This is very true.

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Speaker 1: We all got sent home and we just started buying

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Speaker 1: and buying and buying. I remember early on in the

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Speaker 1: pandemic when there was no paper towels, no toilet paper,

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Speaker 1: no flour, no eggs, no nothing in the grocery store.

445
00:21:41,720 --> 00:21:44,520
Speaker 1: I was trying to buy paper towels offline, and the

446
00:21:44,600 --> 00:21:48,320
Speaker 1: shipping cost was like ninety dollars to ship a few

447
00:21:48,400 --> 00:21:49,640
Speaker 1: rolls of paper calculus.

448
00:21:49,640 --> 00:21:51,679
Speaker 3: I couldn't believe it. I really couldn't believe it. I

449
00:21:51,720 --> 00:21:52,680
Speaker 3: did not purchase them.

450
00:21:52,680 --> 00:21:57,440
Speaker 2: To be clear, there's a baseline supply and demand in economics, right,

451
00:21:57,480 --> 00:21:59,479
Speaker 2: so when there's a lot of supply for a product,

452
00:21:59,480 --> 00:22:03,119
Speaker 2: the price goes down. Demand drives prices to increase, but

453
00:22:03,320 --> 00:22:06,520
Speaker 2: Supply and demand don't exist in isolation. The supply has

454
00:22:06,560 --> 00:22:08,440
Speaker 2: to get to you, right, and so even when there's

455
00:22:08,480 --> 00:22:10,640
Speaker 2: a lot of supply, if we can't get it from

456
00:22:10,640 --> 00:22:13,240
Speaker 2: one place to another. So if there's a supply and

457
00:22:13,280 --> 00:22:15,240
Speaker 2: demand shortage for truckers, right, So if there are not

458
00:22:15,280 --> 00:22:17,399
Speaker 2: a lot of truckers, the demand is no longer on

459
00:22:17,480 --> 00:22:19,879
Speaker 2: the product, the demand is on the transportation. And so

460
00:22:20,000 --> 00:22:25,320
Speaker 2: that's why TT saw that really high shipping costs. But

461
00:22:25,359 --> 00:22:27,360
Speaker 2: when you go back and really think about it, if

462
00:22:27,359 --> 00:22:29,679
Speaker 2: we look at the really big picture, I feel like

463
00:22:29,720 --> 00:22:32,439
Speaker 2: there were some acute things that we felt from the

464
00:22:32,440 --> 00:22:36,200
Speaker 2: pandemic and shipping and demand for online shopping, but when

465
00:22:36,240 --> 00:22:38,879
Speaker 2: we zoom out, there had really been a major shift

466
00:22:38,880 --> 00:22:42,159
Speaker 2: to online shopping even before the pandemic too. That's a

467
00:22:42,200 --> 00:22:44,160
Speaker 2: really good point and we are going to talk about

468
00:22:44,160 --> 00:22:46,600
Speaker 2: that later this season, So be on your p's and

469
00:22:46,640 --> 00:22:49,760
Speaker 2: q's ready for that. And it makes sense too, because

470
00:22:49,800 --> 00:22:54,760
Speaker 2: we are creatures of yes, habit, but more than habit convenience. Okay,

471
00:22:54,800 --> 00:22:57,600
Speaker 2: we want to have what we want when we want it,

472
00:22:57,680 --> 00:23:01,240
Speaker 2: end at our doorsteps, preach. So if there's an option

473
00:23:01,280 --> 00:23:02,920
Speaker 2: for me to have to travel to the store, wait

474
00:23:02,960 --> 00:23:05,240
Speaker 2: in line at the counter. Hope they have what I need,

475
00:23:05,400 --> 00:23:08,760
Speaker 2: Especially for boring purchases. I'd rather add all that stuff

476
00:23:08,800 --> 00:23:10,640
Speaker 2: to Kart and have it delivered to me.

477
00:23:10,720 --> 00:23:12,760
Speaker 3: And with free shipping and free returns.

478
00:23:12,800 --> 00:23:16,040
Speaker 1: At a lot of online retailers, it's so easy to

479
00:23:16,160 --> 00:23:18,880
Speaker 1: add to KRT and check out. But maybe we need

480
00:23:18,880 --> 00:23:22,360
Speaker 1: to start, you know, taking a beat mefore doing that,

481
00:23:22,720 --> 00:23:26,520
Speaker 1: and ask ourselves if we can get by without that purchase.

482
00:23:26,680 --> 00:23:30,320
Speaker 2: Yeah, maybe I don't need all these different Trani syrups

483
00:23:30,359 --> 00:23:34,920
Speaker 2: to make, you know, cafe quality pumpkin spice lattes at home.

484
00:23:35,640 --> 00:23:38,760
Speaker 2: I don't need it, You don't, I don't, I really don't.

485
00:23:38,840 --> 00:23:46,440
Speaker 3: Oh, and this leads us to the elephant in the room. Amazon.

486
00:23:46,800 --> 00:23:50,360
Speaker 1: It feels like you can get anything, literally anything delivered

487
00:23:50,359 --> 00:23:54,080
Speaker 1: to your house in the maximum two days. I've gotten

488
00:23:54,119 --> 00:23:58,080
Speaker 1: things off Amazon and gotten it just a few hours later.

489
00:23:58,400 --> 00:23:59,919
Speaker 1: How are they able to do this?

490
00:24:00,359 --> 00:24:00,439
Speaker 3: So?

491
00:24:00,600 --> 00:24:05,200
Speaker 4: Amazon, their whole modus operandi is that they're going to

492
00:24:05,240 --> 00:24:07,720
Speaker 4: squeeze as much as they can out of workers using

493
00:24:07,920 --> 00:24:10,520
Speaker 4: surveillance technology management by algorithm.

494
00:24:10,720 --> 00:24:14,119
Speaker 2: Amazon famously employs the use of scientific management for all

495
00:24:14,160 --> 00:24:17,600
Speaker 2: of its employees, specifically those working in the fulfillment centers, though,

496
00:24:17,640 --> 00:24:21,280
Speaker 2: workers have to meet certain productivity quotas or face termination.

497
00:24:21,520 --> 00:24:24,920
Speaker 2: And in twenty nineteen, Amazon warehouse workers went on strike

498
00:24:25,040 --> 00:24:28,320
Speaker 2: to protest inhumane working conditions. At the end of October,

499
00:24:28,359 --> 00:24:32,880
Speaker 2: warehouse workers from Amazon's Staten Island facility filed a petition

500
00:24:33,000 --> 00:24:35,320
Speaker 2: for a union election and the request has to be

501
00:24:35,359 --> 00:24:39,000
Speaker 2: approved by the National Labor Relations Board. And this would

502
00:24:39,000 --> 00:24:43,560
Speaker 2: be the second unionization vote, after the workers in Bessemer, Alabama,

503
00:24:43,840 --> 00:24:47,199
Speaker 2: failed to reach enough votes to unionize last April. And

504
00:24:47,560 --> 00:24:50,160
Speaker 2: that's just the tip of the iceberg. We've seen many

505
00:24:50,240 --> 00:24:54,440
Speaker 2: labor stories just like this in so many different sectors, restaurants,

506
00:24:54,440 --> 00:24:57,680
Speaker 2: food delivery, riot sharing, and of course trucking.

507
00:24:57,800 --> 00:25:00,400
Speaker 3: And this is not a good look.

508
00:25:00,600 --> 00:25:03,360
Speaker 1: Amazon has not just been under fire by the media,

509
00:25:03,440 --> 00:25:06,840
Speaker 1: They've also been scrutinized by regulating organizations.

510
00:25:07,080 --> 00:25:10,639
Speaker 4: California just past a bill limiting the use of the

511
00:25:10,720 --> 00:25:13,960
Speaker 4: kind of work quotas that Amazon relies on inside of

512
00:25:13,960 --> 00:25:16,840
Speaker 4: its warehouses. But this whole system of scientific management, or

513
00:25:16,880 --> 00:25:19,879
Speaker 4: as I call it, buzoicism, which is scientific management, plus

514
00:25:19,920 --> 00:25:24,040
Speaker 4: all this technology impacts every other type of worker at Amazon,

515
00:25:24,160 --> 00:25:26,400
Speaker 4: all the way down to the last mile truck drivers.

516
00:25:26,800 --> 00:25:30,800
Speaker 4: Those drivers are subject to the same kind of surveillance

517
00:25:30,840 --> 00:25:33,720
Speaker 4: as the workers in warehouses. There's cameras facing them, cameras

518
00:25:33,760 --> 00:25:36,359
Speaker 4: watching the road, and Amazon says that's all about increasing safety,

519
00:25:36,400 --> 00:25:38,480
Speaker 4: which I'm sure is true, but it's also about making

520
00:25:38,520 --> 00:25:40,800
Speaker 4: sure that they work as quickly as possible.

521
00:25:40,920 --> 00:25:43,960
Speaker 1: And we learn that those drivers don't even work for Amazon.

522
00:25:44,080 --> 00:25:48,200
Speaker 1: They're subcontractors working for smaller trucking companies who work for Amazon.

523
00:25:48,320 --> 00:25:52,160
Speaker 1: And this protects Amazon from any legal liability if.

524
00:25:52,080 --> 00:25:54,240
Speaker 4: One of those trucks gets into an accident. Amazon's not

525
00:25:54,280 --> 00:25:57,160
Speaker 4: directly responsible for that truck. If one of those workers

526
00:25:57,160 --> 00:25:59,679
Speaker 4: gets harassed by their boss, Amazon doesn't have to get

527
00:25:59,720 --> 00:26:01,600
Speaker 4: involve and they can't be sued for it.

528
00:26:01,640 --> 00:26:04,320
Speaker 2: This is like a tefline coding, like a business version

529
00:26:04,359 --> 00:26:06,439
Speaker 2: of it. And since the spring, Amazon has announced some

530
00:26:06,520 --> 00:26:09,080
Speaker 2: changes to address some of the issues in their warehouses,

531
00:26:09,280 --> 00:26:11,480
Speaker 2: so they know they're there. But that includes spending like

532
00:26:11,520 --> 00:26:15,000
Speaker 2: three hundred million dollars on employee safety, but unfortunately it

533
00:26:15,119 --> 00:26:22,359
Speaker 2: still doesn't include driver safety.

534
00:26:23,920 --> 00:26:24,720
Speaker 3: So what's next.

535
00:26:24,800 --> 00:26:26,480
Speaker 1: I mean, I feel like all of this goes back

536
00:26:26,520 --> 00:26:29,879
Speaker 1: to the rise in the gig economy, and Christopher calls

537
00:26:29,960 --> 00:26:32,280
Speaker 1: this the fissured workplace.

538
00:26:31,800 --> 00:26:35,159
Speaker 4: It just means there's more layers between the worker and

539
00:26:35,200 --> 00:26:37,040
Speaker 4: the people who hire those workers.

540
00:26:37,160 --> 00:26:40,880
Speaker 2: So companies like Uber, Lift, Door, Dash, they're all leveraging

541
00:26:40,920 --> 00:26:45,480
Speaker 2: technology using principles of scientific management, but ultimately for profit.

542
00:26:45,520 --> 00:26:49,480
Speaker 4: It's about using technology to take advantage of our existing

543
00:26:49,600 --> 00:26:52,399
Speaker 4: systems of laws. We are going to use all this

544
00:26:52,520 --> 00:26:56,119
Speaker 4: venture capitalists, dough and this technology to rush into the

545
00:26:56,240 --> 00:27:00,480
Speaker 4: vacuum of inadequate regulation in a particular and just to

546
00:27:00,520 --> 00:27:03,280
Speaker 4: try to extract as much profits and kind of mind

547
00:27:03,359 --> 00:27:06,120
Speaker 4: them from the employees that we have. And to be clear,

548
00:27:06,320 --> 00:27:09,440
Speaker 4: you know, I'm not against totally new models like Uber

549
00:27:09,480 --> 00:27:11,880
Speaker 4: and left Like, I think it's cool, maybe there's some

550
00:27:12,080 --> 00:27:14,760
Speaker 4: universe in which it could work, but making sure that

551
00:27:14,800 --> 00:27:17,400
Speaker 4: there are sort of minimum protections for workers. Not only

552
00:27:17,520 --> 00:27:19,000
Speaker 4: is it the humane thing to do, but in the

553
00:27:19,000 --> 00:27:21,480
Speaker 4: long run, it's probably the most sustainable thing to do

554
00:27:22,080 --> 00:27:24,800
Speaker 4: because it would mean less turnover.

555
00:27:25,119 --> 00:27:28,760
Speaker 1: So what are the implication of today's use of scientific

556
00:27:28,800 --> 00:27:31,880
Speaker 1: management more broadly for people working in the United States?

557
00:27:32,080 --> 00:27:34,480
Speaker 4: The overall trend is if you look at like the

558
00:27:34,520 --> 00:27:37,960
Speaker 4: distribution of income in America and the kind of jobs

559
00:27:38,040 --> 00:27:41,159
Speaker 4: people go into, you have more and more people moving

560
00:27:41,160 --> 00:27:43,639
Speaker 4: into more skilled jobs that demand more of them and

561
00:27:43,680 --> 00:27:45,800
Speaker 4: pay them more, but also more and more people moving

562
00:27:45,840 --> 00:27:48,400
Speaker 4: into low skilled jobs where if you have high school

563
00:27:48,480 --> 00:27:50,800
Speaker 4: education or less, your options are very limited.

564
00:27:50,920 --> 00:27:52,000
Speaker 2: That's called de skilling.

565
00:27:52,160 --> 00:27:55,920
Speaker 4: So you kind of hollow out America's middle class and

566
00:27:55,960 --> 00:28:00,000
Speaker 4: you create these two polarized classes of workers.

567
00:28:00,000 --> 00:28:01,439
Speaker 2: Feels like you get to this place where there are

568
00:28:01,480 --> 00:28:04,520
Speaker 2: engineers and developers who are creating the technology to replace

569
00:28:04,560 --> 00:28:06,440
Speaker 2: the jobs that people used to do, and then there's

570
00:28:06,480 --> 00:28:07,600
Speaker 2: just everybody else.

571
00:28:07,440 --> 00:28:10,720
Speaker 4: Which frankly is the majority of American workers who then

572
00:28:10,840 --> 00:28:13,840
Speaker 4: are forced to work alongside that automation or become a

573
00:28:13,880 --> 00:28:15,919
Speaker 4: part of it. I kind of picture them like bugs

574
00:28:15,920 --> 00:28:19,199
Speaker 4: and amber, and they're just trapped in this matrix that

575
00:28:19,320 --> 00:28:22,000
Speaker 4: has been created that's all machines. And it's like, Okay,

576
00:28:22,000 --> 00:28:23,520
Speaker 4: if you're going to function in this world, you have

577
00:28:23,560 --> 00:28:25,439
Speaker 4: to operate like a machine. You have to operate at

578
00:28:25,480 --> 00:28:27,120
Speaker 4: the pace of a machine. You have to do repetitive

579
00:28:27,160 --> 00:28:29,760
Speaker 4: labor like a machine. And to be clear, it's not new, right,

580
00:28:29,800 --> 00:28:32,720
Speaker 4: this is as old as the assembly line and industrialization,

581
00:28:32,920 --> 00:28:36,919
Speaker 4: but this type of work has spread beyond the factory

582
00:28:37,080 --> 00:28:39,640
Speaker 4: to so many other types of labor.

583
00:28:39,920 --> 00:28:43,520
Speaker 1: So when workers are being exploited and their privacy is

584
00:28:43,560 --> 00:28:47,720
Speaker 1: being infringed upon. Those are definitely signs that the scientific

585
00:28:47,760 --> 00:28:52,000
Speaker 1: management practices that they're using have gone overboard. Humans are

586
00:28:52,000 --> 00:28:55,200
Speaker 1: not robots, and we can't ignore our own humanity and

587
00:28:55,240 --> 00:28:57,520
Speaker 1: the humanity of other people while we're in the workplace.

588
00:28:57,640 --> 00:29:00,719
Speaker 2: That's so true, and it feels like this really big

589
00:29:01,120 --> 00:29:04,320
Speaker 2: concept to wrestle with. Right. Yes, I understand these things

590
00:29:04,320 --> 00:29:06,320
Speaker 2: at the different levels of the supply chain, but then

591
00:29:06,360 --> 00:29:09,160
Speaker 2: we still have certain basic needs, right, And so then

592
00:29:09,200 --> 00:29:11,240
Speaker 2: you begin to ask yourself, like, what can I do

593
00:29:11,440 --> 00:29:13,960
Speaker 2: on an individual level to affect some type of change?

594
00:29:14,120 --> 00:29:14,320
Speaker 3: Right?

595
00:29:14,480 --> 00:29:19,160
Speaker 1: Because we're just one consumer and this whole big consumer machine. Right,

596
00:29:19,280 --> 00:29:20,880
Speaker 1: it doesn't feel like there's a lot that we can

597
00:29:20,960 --> 00:29:23,719
Speaker 1: do to make any type of significant change.

598
00:29:23,720 --> 00:29:25,640
Speaker 3: And what we know is a flawed system.

599
00:29:25,800 --> 00:29:28,560
Speaker 4: I mean, I think of it like climate change in

600
00:29:28,600 --> 00:29:30,719
Speaker 4: a way. I think we get really hung up on

601
00:29:31,000 --> 00:29:34,160
Speaker 4: the individual choices that we make. And those individual choices

602
00:29:34,240 --> 00:29:38,040
Speaker 4: are important because they change our mindset and that changes

603
00:29:38,080 --> 00:29:40,080
Speaker 4: how we interact with the world. But in terms of

604
00:29:40,120 --> 00:29:42,760
Speaker 4: having an impact beyond the individual choices that we make,

605
00:29:43,080 --> 00:29:45,280
Speaker 4: you know, I think we all just have to vote

606
00:29:45,520 --> 00:29:50,960
Speaker 4: and be involved civically and advocate for better policy. And

607
00:29:51,120 --> 00:29:53,120
Speaker 4: it doesn't always have to happen at the federal level.

608
00:29:53,240 --> 00:29:56,880
Speaker 4: I mean, California has this incredible power to set the

609
00:29:57,000 --> 00:29:59,680
Speaker 4: gender for the whole country, whether it's emission standards or

610
00:29:59,680 --> 00:30:02,560
Speaker 4: these new laws governing how work is done at Amazon warehouses.

611
00:30:02,640 --> 00:30:06,360
Speaker 4: So sometimes individual states, even cities have the power to

612
00:30:06,680 --> 00:30:08,880
Speaker 4: set a floor on how much money an Uber driver

613
00:30:08,960 --> 00:30:12,360
Speaker 4: gets paid every hour. There's always these kind of opportunities

614
00:30:12,440 --> 00:30:13,200
Speaker 4: to get engaged.

615
00:30:19,400 --> 00:30:21,640
Speaker 2: I think I feeling a little bit more hopeful. I

616
00:30:21,680 --> 00:30:24,040
Speaker 2: have a better understanding of what's going on.

617
00:30:24,280 --> 00:30:25,320
Speaker 3: Yes, the more you know.

618
00:30:25,640 --> 00:30:28,360
Speaker 2: In mid October, the President made a statement about all

619
00:30:28,360 --> 00:30:31,760
Speaker 2: the supply chain issues, and they're talking about leaving the

620
00:30:31,800 --> 00:30:34,840
Speaker 2: ports open, having them running twenty four to seven, shifting

621
00:30:34,920 --> 00:30:38,320
Speaker 2: to some night work based on what we learned from Christopher.

622
00:30:38,400 --> 00:30:40,080
Speaker 2: I don't know how much of a change that's going

623
00:30:40,120 --> 00:30:42,240
Speaker 2: to make, because it seems like there's issues at many

624
00:30:42,240 --> 00:30:44,880
Speaker 2: different steps. But I think if people can kind of

625
00:30:45,160 --> 00:30:47,000
Speaker 2: know what's happening. I've seen it in the news a

626
00:30:47,040 --> 00:30:49,360
Speaker 2: little bit more, we can kind of temper that rush

627
00:30:49,400 --> 00:30:51,320
Speaker 2: when people feel like, Oh, something's happening. I didn't know

628
00:30:51,400 --> 00:30:53,440
Speaker 2: this was going on. It's like when there's a shortage

629
00:30:53,480 --> 00:30:55,440
Speaker 2: of gas and then everybody runs out to get gas

630
00:30:55,560 --> 00:30:57,120
Speaker 2: and it makes it worse. You know. I feel like

631
00:30:57,160 --> 00:30:59,400
Speaker 2: this could be a little bit better. Things could maybe

632
00:30:59,400 --> 00:31:01,680
Speaker 2: be moving slow, but we know that things will come.

633
00:31:01,840 --> 00:31:03,960
Speaker 1: So since tomorrow's Black Friday, how do we want to

634
00:31:04,080 --> 00:31:06,480
Speaker 1: approach it? Now that we know all this stuff that

635
00:31:06,520 --> 00:31:09,080
Speaker 1: we know from Christopher? I think for me, I've never

636
00:31:09,240 --> 00:31:12,000
Speaker 1: gone out to the store and you know, stood in

637
00:31:12,040 --> 00:31:13,240
Speaker 1: the lines for Black Friday.

638
00:31:13,240 --> 00:31:14,640
Speaker 3: But I know a lot of people that do.

639
00:31:15,000 --> 00:31:16,600
Speaker 1: And I think one thing that I might try and

640
00:31:16,640 --> 00:31:20,360
Speaker 1: do is maybe buy locally, like go out to a

641
00:31:20,440 --> 00:31:23,760
Speaker 1: local shop in my neighborhood and try and find, you know,

642
00:31:23,880 --> 00:31:27,120
Speaker 1: gifts from there, or maybe just cut back on the

643
00:31:27,240 --> 00:31:29,480
Speaker 1: amount of gifts that I feel like I need to buy.

644
00:31:29,480 --> 00:31:32,120
Speaker 2: Folks, I'm right with you. I'm all for cutting back

645
00:31:32,120 --> 00:31:34,000
Speaker 2: on the gifts. I feel like, you know, in the

646
00:31:34,000 --> 00:31:35,680
Speaker 2: past couple of years, it really kind of got out

647
00:31:35,680 --> 00:31:38,520
Speaker 2: of control. I'm also going to try to you know,

648
00:31:38,600 --> 00:31:41,360
Speaker 2: when I am purchasing things, I don't need that stuff

649
00:31:41,400 --> 00:31:43,880
Speaker 2: next day, I don't need that stuff in two days.

650
00:31:44,080 --> 00:31:46,360
Speaker 2: Let it come whenever it comes, you know. I think

651
00:31:46,400 --> 00:31:48,360
Speaker 2: if we could ease some of the demand in that

652
00:31:48,480 --> 00:31:50,920
Speaker 2: space as well. I think that could be useful too.

653
00:31:51,160 --> 00:31:53,360
Speaker 1: Or you know, maybe you don't need it at all,

654
00:31:53,920 --> 00:31:57,360
Speaker 1: and that is a very removed from call good point.

655
00:32:00,920 --> 00:32:02,520
Speaker 2: All right, we've been doing a lot of talking, but

656
00:32:02,600 --> 00:32:05,280
Speaker 2: now it's time to hear from you. We're going to

657
00:32:05,320 --> 00:32:07,440
Speaker 2: do a little pop quiz to see just how well

658
00:32:07,480 --> 00:32:09,959
Speaker 2: you've been listening. So look at your Spotify app and

659
00:32:10,040 --> 00:32:12,200
Speaker 2: you should see a poll pop up, ready for the

660
00:32:12,280 --> 00:32:14,880
Speaker 2: question give it to them tt So the question.

661
00:32:14,720 --> 00:32:18,520
Speaker 3: Is what event led to the creation of the shipping container?

662
00:32:18,920 --> 00:32:20,280
Speaker 2: I wonder how many of them are going to get

663
00:32:20,280 --> 00:32:20,560
Speaker 2: it right.

664
00:32:20,880 --> 00:32:22,720
Speaker 3: They're smart. I think that all of them are gonna

665
00:32:22,720 --> 00:32:23,160
Speaker 3: get it right.

666
00:32:23,360 --> 00:32:25,280
Speaker 1: Don't be that guy where you're just gonna choose the

667
00:32:25,280 --> 00:32:27,240
Speaker 1: wrong answer to be funny.

668
00:32:27,960 --> 00:32:28,560
Speaker 2: Is there great?

669
00:32:29,880 --> 00:32:32,959
Speaker 3: You're gonna fail to be funny? I feel like my

670
00:32:32,960 --> 00:32:34,240
Speaker 3: mom has said that to me before.

671
00:32:38,120 --> 00:32:39,560
Speaker 2: All right, it's time for our one thing.

672
00:32:39,840 --> 00:32:42,280
Speaker 3: My one thing this week is the session. I know

673
00:32:42,360 --> 00:32:43,320
Speaker 3: I'm late to the game.

674
00:32:43,360 --> 00:32:45,440
Speaker 1: Most of you have already been watching it, but I

675
00:32:45,480 --> 00:32:46,600
Speaker 1: had not even heard of the show.

676
00:32:46,640 --> 00:32:47,040
Speaker 2: What happened?

677
00:32:47,040 --> 00:32:48,880
Speaker 1: Why weren't y'all on my DM telling me? I think

678
00:32:48,920 --> 00:32:51,240
Speaker 1: I told you about this, Yes, run, but you watch

679
00:32:51,240 --> 00:32:53,719
Speaker 1: a lot of stuff and so sometimes I'm just like,

680
00:32:54,200 --> 00:32:56,200
Speaker 1: you know, he's not going to be able to keep up.

681
00:32:56,360 --> 00:32:58,640
Speaker 1: But I've been watching se session and I have been

682
00:32:58,960 --> 00:33:01,760
Speaker 1: love being it. I'm y'all on at the screen every

683
00:33:01,800 --> 00:33:02,320
Speaker 1: single day.

684
00:33:02,400 --> 00:33:05,080
Speaker 2: Oh my goodness, I'm glad you like it. My one

685
00:33:05,120 --> 00:33:08,120
Speaker 2: thing this week is a book called Good Morning, Monster

686
00:33:09,160 --> 00:33:13,240
Speaker 2: and Baby. It is a profile of five different patients

687
00:33:13,240 --> 00:33:16,120
Speaker 2: from a therapist. There's so much to learn in there.

688
00:33:16,200 --> 00:33:18,760
Speaker 2: It's jam packed. I've been telling everybody all about it,

689
00:33:18,920 --> 00:33:20,920
Speaker 2: Good Morning Monster. Check it out. See if it's at

690
00:33:20,960 --> 00:33:23,000
Speaker 2: your local library, or if you can listen to it

691
00:33:23,040 --> 00:33:24,640
Speaker 2: if you don't want to get a copy. There's something

692
00:33:24,640 --> 00:33:25,760
Speaker 2: to learn for everybody.

693
00:33:25,840 --> 00:33:29,800
Speaker 1: Okay, I'm going to be on top of that.

694
00:33:29,800 --> 00:33:31,880
Speaker 2: That's it for Lap thirty nine. We want to hear

695
00:33:31,920 --> 00:33:33,920
Speaker 2: from you. Call us at two O two five six

696
00:33:34,040 --> 00:33:36,560
Speaker 2: seven seven zero two eight and tell us what you thought,

697
00:33:36,840 --> 00:33:38,400
Speaker 2: or if you have an idea for a lap we

698
00:33:38,400 --> 00:33:40,920
Speaker 2: should do this semester. Tell us that too. We really

699
00:33:40,960 --> 00:33:43,160
Speaker 2: love hearing from you. That's two O two five six

700
00:33:43,240 --> 00:33:44,560
Speaker 2: seven seven zero two eight.

701
00:33:44,720 --> 00:33:47,000
Speaker 1: And don't forget there's so much more for you to

702
00:33:47,040 --> 00:33:49,560
Speaker 1: dig into on our website. There'll be a cheat cheat

703
00:33:49,600 --> 00:33:52,440
Speaker 1: there for Today's lab and additional links and resources in

704
00:33:52,440 --> 00:33:55,160
Speaker 1: the show notes. Plus, you can sign up for our newsletter,

705
00:33:55,240 --> 00:33:57,880
Speaker 1: so check it out at Dope Last podcast dot com.

706
00:33:57,960 --> 00:34:00,600
Speaker 2: And don't forget, Semester four is going to be exclusive

707
00:34:00,720 --> 00:34:04,280
Speaker 2: to Spotify for free starting December sixteenth, So if you

708
00:34:04,320 --> 00:34:06,920
Speaker 2: already listen to us on Spotify, keep doing what you're doing,

709
00:34:06,960 --> 00:34:08,960
Speaker 2: and don't forget to follow Dope Labs and tap the

710
00:34:08,960 --> 00:34:11,920
Speaker 2: bill icon so you never missed when an episode drops.

711
00:34:12,080 --> 00:34:14,480
Speaker 2: Now after December sixteenth, you won't be able to hear

712
00:34:14,600 --> 00:34:17,239
Speaker 2: new episodes of Dope Labs anywhere else, So if you

713
00:34:17,280 --> 00:34:19,640
Speaker 2: don't listen to us on Spotify, be sure to follow

714
00:34:19,719 --> 00:34:21,399
Speaker 2: us on over here, where you can listen to Dope

715
00:34:21,440 --> 00:34:24,360
Speaker 2: Labs plus all of your other favorite shows for free.

716
00:34:24,600 --> 00:34:27,240
Speaker 1: Special thanks to Today's expert Christopher Memes.

717
00:34:27,280 --> 00:34:30,440
Speaker 2: His new book Arriving Today is out now from HarperCollins.

718
00:34:30,520 --> 00:34:33,800
Speaker 2: You can follow him on Twitter at mems m ims.

719
00:34:34,280 --> 00:34:37,399
Speaker 1: Dope Labs is a Spotify original production from Mega Own

720
00:34:37,480 --> 00:34:38,040
Speaker 1: Media Group.

721
00:34:38,160 --> 00:34:41,080
Speaker 2: Our producers are Jenny Ratolck Mast and Lydia Smith of

722
00:34:41,160 --> 00:34:42,920
Speaker 2: WaveRunner Studios.

723
00:34:42,560 --> 00:34:44,640
Speaker 3: Editing in Sound design by Rob.

724
00:34:44,440 --> 00:34:47,000
Speaker 2: Smerciak, mixing by Hannes Brown.

725
00:34:47,120 --> 00:34:51,000
Speaker 1: Original music composed and produced by Taka Yasuzawa and Alex

726
00:34:51,080 --> 00:34:54,719
Speaker 1: Sugier from Spotify. Our executive producer is Gina Delvack, and

727
00:34:54,800 --> 00:34:58,760
Speaker 1: creative producers are Baron Farmer and Candace Manriquez RINN Special

728
00:34:58,840 --> 00:35:03,000
Speaker 1: thanks to Shirley Ramo Yasmin of Fifi, Camu Elolia, Till

729
00:35:03,080 --> 00:35:06,399
Speaker 1: krat Key and Brian Marquis. Executive producers from Mega Own

730
00:35:06,440 --> 00:35:09,120
Speaker 1: Media Group r us T T Show Dia and Zekiah

731
00:35:09,160 --> 00:35:16,799
Speaker 1: Wattley