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Speaker 1: There Are No Girls on the Internet, as a production

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Speaker 1: of iHeartRadio and Unbossed Creative. I'm Bridget Toad and this

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Speaker 1: is there Are No Girls on the Internet. Have you

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Speaker 1: ever heard the phrase so and so is the Internet's

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Speaker 1: main character for the day. That's when somebody does something

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Speaker 1: that everybody is talking about and they become social media's

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Speaker 1: main character. The Internet really has this way of flattening

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Speaker 1: people out, turning them into characters, and then just kind

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Speaker 1: of forgetting about them once they're fifteen minutes of fame

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Speaker 1: is over. But on a new podcast from our buds

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Speaker 1: over at cool Zone called The Sixteenth Minute Friend of

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Speaker 1: the Show, Jamie Loftus explores what happens in that sixteenth minute,

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Speaker 1: who these people are, and what their Internet fame or

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Speaker 1: infamy says about us as a culture. I joined Jamie

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Speaker 1: to discuss an Internet main character that we actually talked

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Speaker 1: about here on There Are No Girls on the Internet.

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Speaker 1: That lady who everybody got mad about after she tweeted

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Speaker 1: about really enjoying her mornings drinking coffee with her husband

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Speaker 1: in her garden.

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Speaker 2: Remember her.

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Speaker 1: It's a story that I think really illustrates a lot

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Speaker 1: about how we're all coping these days, so check it

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Speaker 1: out and be sure to subscribe to the sixteenth minute.

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Speaker 3: Cool Zone Media.

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Speaker 4: Okay, I don't know if you've heard this one, but

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Speaker 4: being a woman on the internet sucks. It is bad.

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Speaker 4: It is so bad that maybe you just rolled your

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Speaker 4: eyes at hearing me say it, like, well, a white

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Speaker 4: millennial just said being a woman online is actually really hard,

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Speaker 4: and not to be that brave white millennial, but yes,

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Speaker 4: it really sucks being a woman on the internet, and

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Speaker 4: it sucks so much that it's bad writing for me

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Speaker 4: to even tell you that. But if you're a woman, girl,

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Speaker 4: non binary, really just not a cis man online and

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Speaker 4: other random online users know that, particularly anonymous people, you'll

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Speaker 4: get a crash course in gender discrimination the likes of

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Speaker 4: which you could not imagine. And of course this happens

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Speaker 4: across many lines, and intersecting marginalized identities tends to mean

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Speaker 4: worse abuse. That's why we have terms like misogenre to

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Speaker 4: describe the elevated prejudice that black women experience, or why

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Speaker 4: a study from the National Library of Medicine found that

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Speaker 4: gendered racism against Asian American women has gotten worse in

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Speaker 4: recent years, causing a community wide decrease in mental health.

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Speaker 4: Trans women face threats of violence and violent actions at

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Speaker 4: four times the rate of CIS women, compounded by the

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Speaker 4: world's most powerful countries passing laws that invalidate their existence

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Speaker 4: at best and enable transgenocide at worst. And that's just

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Speaker 4: studies that address people who identify as women. Non Binary

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Speaker 4: people face a whole separate type of discrimination. There's billions

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Speaker 4: of ways to be a woman online and most of

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Speaker 4: them fucking suck. And that's because being a woman anywhere

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Speaker 4: still tends to fucking suck. That's one of the first

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Speaker 4: things you learn on the internet. Don't be marginalized in

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Speaker 4: any way, or someone's gonna threaten to kill you. You

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Speaker 4: could also fall in love or meet your best friend

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Speaker 4: in my case, all of the above. That's the monkey

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Speaker 4: paw of logging in. It's why when I was twelve

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Speaker 4: and posting on message boards lying out of my ass,

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Speaker 4: pretending to be a nineteen year old boy named Aaron

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Speaker 4: who wanted to store the band I got legitimate replies

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Speaker 4: and asked what my favorite bands were. And when I

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Speaker 4: panicked and admitted I was a twelve year old girl,

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Speaker 4: the same people started asking me for pictures of myself

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Speaker 4: really cool stuff. And while there were many main characters

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Speaker 4: of the Internet who became notorious or were pilloried for

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Speaker 4: doing something. A father refuses to open a can of

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Speaker 4: beans for his daughter to teach her a lesson. A

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Speaker 4: husband loves his curvw wife a little too weird. And

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Speaker 4: then there are others who become the character of the

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Speaker 4: day for simply existing online. Come with me if you

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Speaker 4: will to October twenty twenty two. Shouldn't be a super

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Speaker 4: heavy lift. You know it's It's not not recent. The

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Speaker 4: day was October twenty first. Kim Kardashian tried to go

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Speaker 4: to a fancy restaurant and an usher concert for her

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Speaker 4: forty second birthday, but ends up at an in and

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Speaker 4: Out instead. Liz Trust becomes the shortest lived UK Prime

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Speaker 4: Minister of all time and resigns after only six weeks.

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Speaker 4: Midnights by Taylor Swift comes out, introducing the extremely unpleasant

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Speaker 4: lyric Someday, I feel like everybody is a sexy baby

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Speaker 4: into the world. Swifties, please don't contact me. I'm having

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Speaker 4: a hard time right now and I can't deal with you. Yes,

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Speaker 4: October twenty twenty two. In two short weeks, I would

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Speaker 4: give a speech at my friend's wedding and meet the

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Speaker 4: man who would ruin my life for the next nine

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Speaker 4: months next to a porta potty. So here's some obvious

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Speaker 4: advice I can give you. Never talk to a man

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Speaker 4: you meet next to a porta potty. The point is

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Speaker 4: being a woman online or in the world, or me specifically,

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Speaker 4: is a pain in the ass, and our main character

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Speaker 4: is terrific. Proof of that with a healthy dose of

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Speaker 4: class dynamic discussion to boot the wife who drank coffee

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Speaker 4: in the garden, Your sixteenth minute begins now. On the

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Speaker 4: morning of October twenty first, twenty twenty two, a twenty

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Speaker 4: four year old woman named Daisy tweeted the following from

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Speaker 4: her Twitter account at Lil Plant Mommy.

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Speaker 3: My husband and I wake up every morning and bring

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Speaker 3: our coffee out to her garden and sit and talk

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Speaker 3: for hours every morning. It never gets old and we

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Speaker 3: never run out of things to talk to.

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Speaker 4: Love him so much, I know, really fucked up stuff.

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Speaker 4: The story here is young woman enjoys coffee and talking

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Speaker 4: with her husband for long periods of time. The reaction

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Speaker 4: to this story, well.

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Speaker 5: I wake up every day with chronic pain.

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Speaker 4: Carcel tunnel syndrome and.

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Speaker 5: Wash my OCD medication down with an iced oat milk lattape.

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Speaker 6: But whatever, potato potato? Am I right? For hours?

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Speaker 4: Put?

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Speaker 6: What if we weren't inherently wealthy and have to work

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Speaker 6: in stuff?

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Speaker 2: Lol?

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Speaker 6: This is cute and all that?

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Speaker 5: Did you think of all the people who wake up

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Speaker 5: to where it grueling hours, wake up on this streets

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Speaker 5: alone or with chronic pain? Before posting this, you should

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Speaker 5: be mindful next time before bragging about your picture perfect life.

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Speaker 5: You might upset someone.

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Speaker 6: What is the purpose of this communication? I'm happy for you,

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Speaker 6: but it's just smug, self satisfied bragging. If it's true,

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Speaker 6: your partner is most likely embarrassed by the tweet, or

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Speaker 6: at least they should be.

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Speaker 5: That is, unless you're flogging something very nice story. But

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Speaker 5: haven't you been married for less than four months? This

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Speaker 5: phase will end, it always does. Please don't be disheartened

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Speaker 5: when it does. Remember love is a choice, not a feeling.

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Speaker 6: No. No, they're a small business owner, so they are

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Speaker 6: actively participating and taking advantage of other people's labors so

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Speaker 6: they can have these blissful mornings. They are capitalism.

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Speaker 4: They are capitalism. They don't even control the railways or

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Speaker 4: the flow of commerce. I know it's not the same thing,

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Speaker 4: but it feels like the same thing. I mean, Twitter

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Speaker 4: is undefeated for finding me only people on earth who

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Speaker 4: can be crueler to you than your own negative self talk.

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Speaker 4: And that's just a fact. But to be honest, I

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Speaker 4: was in a bad enough place when I saw this

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Speaker 4: story that while I recognized that the backlash of this

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Speaker 4: poor woman was ridiculous, I kind of resented her too.

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Speaker 4: Every day I'm doing well financially, but I don't have

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Speaker 4: talking to my partner for hours in the garden every

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Speaker 4: day money. I don't even think I have garden money.

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Speaker 4: And at the time, I hadn't met anyone to either

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Speaker 4: drink coffee with or ruin my life with. But to

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Speaker 4: my credit, I had the wisdom do not participate in

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Speaker 4: this discourse. I did what I think is the much

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Speaker 4: safer move, thought about it privately, and kept my fucking

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Speaker 4: mouth shut. At the time I'm writing this, this tweet

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Speaker 4: from at Little Plant Mommy has three hundred and fourteen

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Speaker 4: thousand likes. This is about as close as it gets

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Speaker 4: to a full on public shaming for saying something that

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Speaker 4: isn't only innocuous on its face, but also doesn't appear

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Speaker 4: to be courting attention outside of Daisy's Twitter circle at

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Speaker 4: this time. I think she technically qualifies as a micro influencer,

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Speaker 4: so less than twenty thousand followers, not just a rando

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Speaker 4: talking to people she only knows in real life, but

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Speaker 4: by no means someone who is courting a massive audience.

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Speaker 4: You probably follow one hundred people like this. I'm basically this,

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Speaker 4: And at the time this tweet was posted, Daisy had

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Speaker 4: a discernible aesthetic and things that she talked to her

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Speaker 4: audience about frequently, So for her, this tweet wouldn't have

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Speaker 4: been outside of the realm of a very normal post

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Speaker 4: that she would make about a year before this, the

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Speaker 4: only other time the Wayback Machine Internet archives saved her page.

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Speaker 4: Daisy's bio read as follows.

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Speaker 3: Naturopathic medicine student, white woman's student emoji, licensed holistic beauty

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Speaker 3: specialist branch emoji, sustainable gardener, white woman gardener emoji.

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Speaker 4: A few months before the tweet that shook the Earth,

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Speaker 4: she got married to a man named Matt who it

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Speaker 4: seems like she loved a whole lot. That's it, and

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Speaker 4: her tweets were maybe what you'd expect based on that

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Speaker 4: pretty niche with a lot of slightly woo woo wellness

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Speaker 4: talk that isn't for everyone, but wasn't trying to be.

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Speaker 4: As I read through some of her old stuff, I

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Speaker 4: didn't agree with some of it. I mean, I don't

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Speaker 4: think dairy is as bad as all that, but honestly,

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Speaker 4: I probably never would have found her account if it

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Speaker 4: weren't for this story. People with as many seven to

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Speaker 4: eleven loyalty points as I do are simply not buying

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Speaker 4: what our girl Daisy is selling. And by the way,

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Speaker 4: the reaction that some of these response tweets imply suggests

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Speaker 4: that Daisy owned a business that personified the grueling puppy

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Speaker 4: mill that is capitalism with the same energy as if

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Speaker 4: she were Jeff Bezos himself. Again, not true. Daisy ran

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Speaker 4: a small time esthetician business called The Holistic Esthetician, and

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Speaker 4: there's nothing wrong with that outside of being a little

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Speaker 4: hard for me to say. It doesn't even seem like

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Speaker 4: she has employees, and that might also explain her flexible hours.

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Speaker 4: And I can't emphasize enough that for this fairly small

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Speaker 4: account less than twenty thousand followers, this was not an

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Speaker 4: unusual post. The tweets posted around the same time were

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Speaker 4: pretty similar.

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Speaker 3: The perfect balance of love and light but also real,

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Speaker 3: raw and imperfect is what I'm always striving for. Balance. Baby,

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Speaker 3: that some highlights and a couple haircuts yesterday after months

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Speaker 3: of not doing hair, and they both turned out so pretty.

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Speaker 3: Makes me missdoing hair?

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Speaker 4: So why did this tweet about drinking coffee in the

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Speaker 4: garden blow up the Twitter algorithm? In a recent episode,

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Speaker 4: I spoke with Taylor Lorenz about the phenomenon of the dress,

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Speaker 4: and while Coffee Wife isn't a story she reported on

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Speaker 4: at the time, she has a lot of experience in

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Speaker 4: tracking stories like this, and what she found instructive about

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Speaker 4: the drinking coffee in the garden story wasn't that it

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Speaker 4: was more upsetting than your average woman doing something and

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Speaker 4: getting yelled at online story. It was that the stories

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Speaker 4: boost in the algorithm required both backlash to what Daisy

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Speaker 4: said and backlash to the backlash. Here's some of our

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Speaker 4: talk about that.

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Speaker 7: Yeah, what was unique about that one too? Or what

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Speaker 7: I think is happening more and more with these newer

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Speaker 7: main characters, and I can think got to say Sidney

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Speaker 7: Sweeny's a good example of this. More recently too. It's

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Speaker 7: like somebody goes viral and everybody projects their ideology onto

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Speaker 7: that person and they become this vehicle for making some

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Speaker 7: point about society. And I think we used to not

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Speaker 7: do that as much with our main characters. I think

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Speaker 7: they were just like we could appreciate that they were

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Speaker 7: funny or they were in a viral video or whatever.

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Speaker 7: And now it's like everything has to say something about

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Speaker 7: the world. And that's what I noticed when that went viral. Initially,

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Speaker 7: people and I.

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Speaker 8: Think I mean districtly based on how the engagement algorithm

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Speaker 8: was working at that time, because a lot of people

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Speaker 8: were like, let's yell at her.

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Speaker 7: Well, but it was not. It was an equal parts

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Speaker 7: let's yell at her and then people getting outraged that

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Speaker 7: people were yelling at her, And that is It's really

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Speaker 7: important to have like both of those, I think, to

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Speaker 7: reach the level of virality that this did. But you

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Speaker 7: know this is right, like since Twitter has been leaning

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Speaker 7: harder and harder into algorithmic recommendations for years, but I

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Speaker 7: think we've really seen it, especially since the Ylon era

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Speaker 7: like really take hold. And I think this is an

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Speaker 7: example of Twitter leaning hard into algorithmic recommendations. Were only

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Speaker 7: this person is in your feed because everybody has an

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Speaker 7: opinion on the commentary about it, and everybody wants to

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Speaker 7: again project, they want to use this innocuous, benign, sort

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Speaker 7: of generic tweet as a way to posture about whatever

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Speaker 7: they want to talk.

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Speaker 8: About totally, and I think, I mean, that's a really

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Speaker 8: great point that, like, you know, the wave of anger

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Speaker 8: towards this user is one thing, but this story doesn't

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Speaker 8: really thrive unless she also has thousands of people coming

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Speaker 8: to her defense, even though she's tweeting, you know, into

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Speaker 8: presumably to her the void. Do you remember when that

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Speaker 8: sort of phenomenon took.

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Speaker 7: Oh yeah, yeah, I was going to write about this

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Speaker 7: recently because there was this sort of similar thing about

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Speaker 7: door dash. Some person talked about DoorDash and suddenly it

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Speaker 7: was like five days of discourse of people outraged about DoorDash,

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Speaker 7: and then people outraged about the outrage. But the outrage

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Speaker 7: at people that are expressing they're very you know, first

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Speaker 7: of all, they shouldn't be expressing it at that woman,

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Speaker 7: But I can understand things are triggering on the internet.

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Speaker 7: Whatever they get triggered, But then it's like the other

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Speaker 7: people getting very triggered that anybody is triggered, and it's

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Speaker 7: just it just goes bananas. But yeah, I mean, I

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Speaker 7: think also just we're dealing with a lot of really

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Speaker 7: big problems in society, and people can't reach the people

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Speaker 7: that actually can affect change, and the people that can

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Speaker 7: affect change and have institutional power don't give a shit

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Speaker 7: what average people have to say if they don't have

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Speaker 7: money or access themselves to power. So these main characters

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Speaker 7: kind of become the only outlet for voicing this anger,

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Speaker 7: and people are used as props to make these arguments

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Speaker 7: or statements or whatever because they're at least accessible.

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Speaker 5: You know.

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Speaker 8: Yeah, how have you seen, as you know, as our

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Speaker 8: feeds become algorithmically driven, how the treatment has changed with

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Speaker 8: regards to gender.

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Speaker 7: Yeah, well, I think actually hatred of women is sort

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Speaker 7: of fueled virality on the Internet for years, and especially

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Speaker 7: since the beginning. I mean, I talk about it in

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Speaker 7: the book, But the people that really pioneered the content

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Speaker 7: creator industry and some of the people that put themselves

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Speaker 7: online first were women. And there's a specific type of

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Speaker 7: woman that gets a lot of hatred, which is sort

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Speaker 7: of a semi attractive or seemingly privileged women usually an

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Speaker 7: upper middle class white woman. In one sense, they do

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Speaker 7: very well on the internet because they ascribe you know,

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Speaker 7: they ascribe to traditional beauty standards. You know, they're usually

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Speaker 7: somewhat attractive, somewhat privileged enough to do well online, or

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Speaker 7: enough to get attention online. But they're also subject to

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Speaker 7: some of the most vicious hate because it's just a

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Speaker 7: favorite pastime of the Internet to tear women down, specifically wives,

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Speaker 7: because there's this notion of like moms and wives like

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Speaker 7: always doing something wrong, or like it's misogyny. I mean,

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Speaker 7: it's just hardcore misogyny, and of course a separate type

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Speaker 7: of really vicious hatred towards women of color or also

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Speaker 7: just ripped apart constantly. The thing is, they don't really

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Speaker 7: have the level of privilege, and so they often some

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Speaker 7: of these wives. Curvey Wife is a good example, right,

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Speaker 7: you know, she's sprung that into brand deals and has

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Speaker 7: a plus size clothing partnerships and all of this. Women

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Speaker 7: of color are not able to take advantage of that

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Speaker 7: virality and monetize it the same way. I mean, this

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Speaker 7: Coffee wife woman doesn't sound like she's leaned into it,

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Speaker 7: but she could have released her own line of coffee

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Speaker 7: cups or whatever you know, like and I don't know

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Speaker 7: what she looks like, but I think like that people

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Speaker 7: are more accepting of privileged women, almost pivoting, even though

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Speaker 7: they receive an outside hatred. If you're a conventionally attractive wife, mother,

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Speaker 7: or seen as a slightly privileged wife and mother, you're

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Speaker 7: gonna get torn apart because that is what like misogynis

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Speaker 7: on the internet. Love to come for Yeah.

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Speaker 4: Thanks again to Taylor. Her book Extremely Online is available now.

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Speaker 4: So talking with Taylor reset how I was thinking about

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Speaker 4: this story a little. So to say that the legacy

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Speaker 4: of Coffee Wife is that people hate women online is

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Speaker 4: technically true, but a little undercooked. After talking to Taylor,

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Speaker 4: I became convinced that this story is also a pretty

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Speaker 4: damning example of modern online algorithms gaming us to engage

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Speaker 4: with each other. Because, as I was going back through

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Speaker 4: the quote tweets reacting to Daisy's bold statement, the mean

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Speaker 4: tweets versus the defenses of Daisy are uneven. There's more

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Speaker 4: nice comments coming to her defense for every tweet that

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Speaker 4: says they are capitalism. There's also this.

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Speaker 6: That lady said she enjoys mornings with her husband and

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Speaker 6: folks said, not on my watch.

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Speaker 4: I can't afford coffee. The only thing I have to

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Speaker 4: drink in the garden is bird bathwater because I'm a robin.

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Speaker 4: I'm an actual bird. This tweet is not relatable to

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Speaker 4: my experience as a literal bird. I can't get a

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Speaker 4: house because I'm a bird and can't apply for a mortgage.

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Speaker 4: Privileged bitch eat.

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Speaker 6: The rich has gone from no one should be a

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Speaker 6: billionaire to no one living above the poverty level treating

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Speaker 6: themselves and their husband to morning coffee in their gardens

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Speaker 6: should be happy.

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Speaker 5: I feel like this is causing so much uproar because

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Speaker 5: so many people are experiencing lovelessness and indifference from people

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Speaker 5: they're even romantically connected with, and seeing someone experience friendship

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Speaker 5: and love that seems calm, balanced and easy is infuriating.

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Speaker 4: And when it comes to the algorithm, once you've got

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Speaker 4: a class war, about the class war, you are cooking.

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Speaker 4: In one of the last interviews Daisy gave on the

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Speaker 4: subject in December twenty twenty two with YouTuber and Jellylooz,

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Speaker 4: she described what it was like experiencing these waves of

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Speaker 4: discourse in what felt like a void.

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Speaker 9: It just kind of like blew up within like ten

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Speaker 9: hours of it posting. I posted it, I noticed that

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Speaker 9: like a lot of people were like commenting and liking it,

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Speaker 9: and it was kind of going a little viral, and

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Speaker 9: like by the next day that I had posted it,

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Speaker 9: it was just like totally blown up with lots of

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Speaker 9: like lots of negativity and lots of like hate comments

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Speaker 9: and people saying all kinds of like crazy stuff about

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Speaker 9: me and my husband, and that kind of continued. The

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Speaker 9: negativity kind of continued for a little bit, but it

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Speaker 9: got to the point by like day like two or

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Speaker 9: three where like everybody was just coming in on the

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Speaker 9: post and being like this is actually so cute and

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Speaker 9: so nice and like forget about all the haters and

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Speaker 9: like all of that stuff. And I feel like, I

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Speaker 9: mean when I try to go into the tweet and

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Speaker 9: like look for the negativity, I literally can't find negative

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Speaker 9: comments anymore because there's been so many thousands of people

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Speaker 9: that have just like drowned all of the like meanness

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Speaker 9: in positivity and kindness and love. And so then I

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Speaker 9: kind of think that it like went in this wave

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Speaker 9: of negativity, and then there was like another way where

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Speaker 9: it was like where it got more popular, but then

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Speaker 9: it was like turned into something really sweet and positive.

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Speaker 4: She goes on to describe the few days of constant

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Speaker 4: attention and requests for comment by embracing the Coffee Lady persona,

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Speaker 4: even briefly adding it to her Twitter bio. And not

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Speaker 4: everyone would be able to do this, but she takes

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Speaker 4: it in stride, leaning into jokes that suggest that this

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Speaker 4: was all some big, evil plan. She tweets things like this,

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Speaker 4: this was all actually a big plot to draw everybody

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Speaker 4: in and then teach them about how to grow their

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Speaker 4: own food and heal the earth plant emoji, and general

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Speaker 4: reflections on the weird, still developing media cycle of those

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Speaker 4: last few days in October. She directly confronts the criticism

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Speaker 4: in a gentle series of tweets.

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Speaker 3: It's really sad to look at the thousands of hateful

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Speaker 3: comments on this post, most saying spending time with your

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Speaker 3: spouse is only for the rich, jobless trust fund kids,

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Speaker 3: saying our marriage don't last. It really shows why a

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Speaker 3: lot of marriages probably don't last. It's one thing to

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Speaker 3: get to spend hours a day with your partner. We

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Speaker 3: are very blessed, But most of the replies are implying

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Speaker 3: that couples shouldn't have to spend time together and if

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Speaker 3: they do, you must be rich.

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Speaker 4: Y'all are truly silly.

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Speaker 3: But thank you to all the sweet comments. I love

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Speaker 3: you so much, double heart emoji.

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Speaker 4: And to directly address her haters who claimed that she

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Speaker 4: was capitalism, Daisy tweeted this.

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Speaker 3: To answer your questions, we are not rich by any means.

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Speaker 3: We've worked extremely hard to get to where we're at.

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Speaker 3: We live very minimally and consciously and work jobs that

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Speaker 3: match our lifestyle and allow us to live the life

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Speaker 3: that we do. Thank you for all the love that

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Speaker 3: uplifting comments. You know who you are, red heart emoji.

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Speaker 4: Daisy threads the needle pretty beautifully here, and I think

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Speaker 4: this is a good example of how women have to

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Speaker 4: conduct themselves very carefully online to not get anger from people.

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Speaker 4: She's not ignoring it, but if it does upset her

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Speaker 4: in any way, which it could be justified to do,

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Speaker 4: she doesn't indicate that publicly. She and her husband post

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Speaker 4: a number of other pictures in their garden, which it

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Speaker 4: turns out is where they live in a community in

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Speaker 4: northern California, where he teaches yoga and she runs her

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Speaker 4: small esthetician business. They tweeted pictures of them eating breakfast,

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Speaker 4: drinking the famous coffee. And while they never dropped their

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Speaker 4: tax returns or the degree of privilege that they grew

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Speaker 4: up with, the question is why should they have to?

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Speaker 4: Because the algorithm said so, There's no way around it.

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Speaker 4: This story was tailor made for the Internet rage machine.

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Speaker 4: Box writer Rebecca Jennings referenced as much in a December

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Speaker 4: twenty twenty two essay called every chronically online conversation is

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Speaker 4: the same, saying if you felt a creeping sense of

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Speaker 4: dread while reading about Daisy and her husband enjoying coffee

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Speaker 4: in their garden, it's possible you spend too much time online.

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Speaker 4: That's because despite it seeming innocuous, Daisy's post has all

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Speaker 4: the markers Twitter rage bait, and by rage bait I

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Speaker 4: mean a person sharing an experience that may not be

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Speaker 4: entirely universal. I mostly agree with this, and do feel

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Speaker 4: that the anger towards Daisy is wildly misplaced. This is

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Speaker 4: the kind of anger we reserve for Kardashians throwing parties

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Speaker 4: during a pandemic, and this doesn't invalidate any of the

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Speaker 4: anger or frustration that online users that were truly sorry.

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Speaker 4: Triggered by Daisy's inoffensive post fault. I mean, hell, Daisy

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Speaker 4: herself articulated this feeling better than anyone else here. She

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Speaker 4: is on that same Angelilou's YouTube podcast.

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Speaker 9: You know, as far as what I could say to

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Speaker 9: the people that were doing all of that is, I

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Speaker 9: just think when you're exuding that much hate to other people,

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Speaker 9: that comes from a place in your heart that's hurt,

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Speaker 9: because I truly believe that you know everything that like,

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Speaker 9: we're all just mirrors of each other, and something about

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Speaker 9: me made them feel something about themselves that was probably

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Speaker 9: trauma from who knows when in their life, and that

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Speaker 9: caused something and caused them to feel that way. So

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Speaker 9: I think that that just comes. That kind of behavior

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Speaker 9: just comes from someone being hurt. And I understand that,

437
00:25:16,040 --> 00:25:20,520
Speaker 9: and I have compassion for those people because truly, maybe

438
00:25:20,520 --> 00:25:22,400
Speaker 9: they know better, but they probably don't know any better,

439
00:25:22,440 --> 00:25:25,200
Speaker 9: but they're just dealing with their hurt and they're dealing

440
00:25:25,200 --> 00:25:28,320
Speaker 9: with it like that instead of in other healthy ways.

441
00:25:28,440 --> 00:25:28,639
Speaker 6: You know.

442
00:25:29,640 --> 00:25:33,600
Speaker 4: So thankfully Coffee Wife had a mellow enough lifestyle to

443
00:25:33,680 --> 00:25:37,760
Speaker 4: forgive and was offline enough to understand the anger without

444
00:25:37,800 --> 00:25:41,560
Speaker 4: becoming enraged back when it comes to women behaving in

445
00:25:41,600 --> 00:25:45,400
Speaker 4: a very particular way to not get a particular reaction.

446
00:25:45,800 --> 00:25:49,920
Speaker 4: Daisy did everything right. All she did wrong was exist

447
00:25:50,000 --> 00:25:53,080
Speaker 4: in a way that the algorithm was liable to boost.

448
00:25:53,720 --> 00:25:56,840
Speaker 4: When I started this show, the person who was most insistent,

449
00:25:56,960 --> 00:26:00,480
Speaker 4: along with hundreds of others, that I talk about coffee

450
00:26:00,920 --> 00:26:03,439
Speaker 4: was my best friend Julia, and I wanted to know why,

451
00:26:03,800 --> 00:26:05,840
Speaker 4: because no matter where you fell at the time, what

452
00:26:05,960 --> 00:26:08,479
Speaker 4: happened over the coffee in the garden tweet was a

453
00:26:08,560 --> 00:26:12,159
Speaker 4: pretty classic public shaming. And Julia is a great comic

454
00:26:12,240 --> 00:26:15,080
Speaker 4: and writer who wrote a controversial essay for Gawker in

455
00:26:15,119 --> 00:26:19,280
Speaker 4: twenty twenty two called in Defense of Shame. She's literally

456
00:26:19,400 --> 00:26:22,360
Speaker 4: an authority on shame, and not just because she grew

457
00:26:22,440 --> 00:26:25,119
Speaker 4: up Catholic in New England. But that certainly didn't hurt,

458
00:26:25,400 --> 00:26:29,679
Speaker 4: and Julia feels strongly that Daisy was not deserving of

459
00:26:29,720 --> 00:26:33,720
Speaker 4: the backlash she got. So when is shame a necessary tool?

460
00:26:34,119 --> 00:26:36,720
Speaker 4: And when is it? Whatever the fuck this is, I

461
00:26:36,760 --> 00:26:38,680
Speaker 4: wanted to ask her about it first.

462
00:26:39,200 --> 00:26:43,640
Speaker 10: I am Julia Claire. I'm a comedian and writer at

463
00:26:43,680 --> 00:26:44,439
Speaker 10: Crooked Media.

464
00:26:45,280 --> 00:26:48,919
Speaker 4: You are the person that I associate most with, like

465
00:26:49,359 --> 00:26:51,040
Speaker 4: intensely feeling about this story.

466
00:26:51,840 --> 00:26:54,320
Speaker 10: I am the person you most associate with the concept

467
00:26:54,320 --> 00:26:54,720
Speaker 10: of shame.

468
00:26:56,000 --> 00:27:00,280
Speaker 4: Yes, yes, and so it really you've saved me an

469
00:27:00,280 --> 00:27:06,000
Speaker 4: interview here, but also because yeah, like you felt really

470
00:27:06,640 --> 00:27:11,399
Speaker 4: strongly that this woman had been shamed improperly, but you

471
00:27:11,520 --> 00:27:14,560
Speaker 4: do feel tell me your feelings about a proper shaming.

472
00:27:14,960 --> 00:27:18,200
Speaker 10: A few years ago, I wrote a piece for gaker

473
00:27:18,440 --> 00:27:23,240
Speaker 10: Rip called in Defense of Shame. Was kind of immediately

474
00:27:23,680 --> 00:27:26,879
Speaker 10: criticized by people who didn't read the piece as a

475
00:27:26,960 --> 00:27:31,520
Speaker 10: defense being a defensive shaming. People were basically saying that

476
00:27:32,119 --> 00:27:37,400
Speaker 10: I was co signing dogpile culture, co signing shaming, which

477
00:27:37,440 --> 00:27:40,439
Speaker 10: is not at all what I was talking about in

478
00:27:40,480 --> 00:27:46,280
Speaker 10: the piece. I think of shame as any lapsed Catholic would.

479
00:27:46,520 --> 00:27:46,639
Speaker 4: Uh.

480
00:27:47,480 --> 00:27:54,119
Speaker 10: It's a very kind of like internal experience, more of

481
00:27:54,160 --> 00:27:58,199
Speaker 10: a reflective experience, not an external experience.

482
00:27:58,920 --> 00:28:00,760
Speaker 2: Shame is for Shame is for me.

483
00:28:00,880 --> 00:28:01,560
Speaker 4: It's not for.

484
00:28:01,520 --> 00:28:08,320
Speaker 10: You, you know, it's like so to me. I mean basically, like,

485
00:28:08,400 --> 00:28:11,199
Speaker 10: my defense of shame was that more people need to

486
00:28:11,200 --> 00:28:14,359
Speaker 10: be kind of in touch with their own shame. And

487
00:28:14,400 --> 00:28:18,239
Speaker 10: I honestly think that like a lot of the I

488
00:28:18,320 --> 00:28:20,080
Speaker 10: think the fact that a lot of people aren't is

489
00:28:20,119 --> 00:28:23,199
Speaker 10: the reason why they end up projecting on other people.

490
00:28:24,040 --> 00:28:29,199
Speaker 10: But yeah, this was one of those things, like that

491
00:28:29,440 --> 00:28:33,560
Speaker 10: was a clear case of shaming in a way that

492
00:28:33,760 --> 00:28:39,480
Speaker 10: was completely needless and silly. Honestly, you're yelling at this

493
00:28:40,080 --> 00:28:44,720
Speaker 10: twenty something woman because she's having a lovely mourning, right,

494
00:28:45,480 --> 00:28:46,360
Speaker 10: kill yourself.

495
00:28:48,840 --> 00:28:54,880
Speaker 4: Is there a productive way to shame someone on the internet.

496
00:28:56,440 --> 00:28:57,840
Speaker 10: That's a really good question.

497
00:28:58,880 --> 00:28:59,960
Speaker 2: I think you have to.

498
00:29:00,480 --> 00:29:03,280
Speaker 10: I think if there is, you really have to be

499
00:29:03,320 --> 00:29:06,320
Speaker 10: punching up. Like the whole thing with Coffee Wife is

500
00:29:06,360 --> 00:29:09,240
Speaker 10: that she was just some kind of like random lady. Right,

501
00:29:09,320 --> 00:29:12,240
Speaker 10: It's very different if we're all piling on to like

502
00:29:12,680 --> 00:29:14,840
Speaker 10: I mean, there are some people who are really impervious

503
00:29:14,920 --> 00:29:19,040
Speaker 10: to it. So it like, you know, Elon Musk seems

504
00:29:19,080 --> 00:29:24,080
Speaker 10: to just revel in the fact that everyone hates him.

505
00:29:25,760 --> 00:29:28,880
Speaker 10: But as far as a productive way to shame, to

506
00:29:28,960 --> 00:29:32,160
Speaker 10: shame the average per I mean, no, I don't think so,

507
00:29:32,280 --> 00:29:35,320
Speaker 10: and I and I really again, I don't advocate for

508
00:29:35,560 --> 00:29:38,920
Speaker 10: shame as an external force. I think all of our

509
00:29:38,960 --> 00:29:43,040
Speaker 10: shame should be internal, and it should be between us

510
00:29:43,120 --> 00:29:47,680
Speaker 10: and the Lord. Your parents are going to be so pleased,

511
00:29:47,800 --> 00:29:52,440
Speaker 10: I know, Father Leroy at Saint Edward's Parish.

512
00:29:52,640 --> 00:29:54,640
Speaker 4: Your impact is felt on this podcast.

513
00:29:54,840 --> 00:29:55,520
Speaker 10: Absolutely.

514
00:29:57,800 --> 00:29:59,760
Speaker 4: Thank you so much to my best friend Julia Claire.

515
00:30:00,200 --> 00:30:03,680
Speaker 4: You can catch every day over at Crooked Media and

516
00:30:03,760 --> 00:30:08,160
Speaker 4: we'll be right back with more of Coffee Wife's sixteenth minute.

517
00:30:08,400 --> 00:30:24,320
Speaker 4: Maybe welcome back to sixteenth minute today. I've had six

518
00:30:24,360 --> 00:30:27,640
Speaker 4: cups of coffee and still no husband in sight. We're

519
00:30:27,680 --> 00:30:31,880
Speaker 4: talking coffee wife. So not to twenty sixteen ghostbusters this situation,

520
00:30:32,320 --> 00:30:34,960
Speaker 4: but take a second to imagine how this story would

521
00:30:35,000 --> 00:30:38,400
Speaker 4: be different if it were a husband tweeting about enjoying

522
00:30:38,440 --> 00:30:42,040
Speaker 4: time with his wife in said garden. I really don't

523
00:30:42,080 --> 00:30:44,480
Speaker 4: think the reaction would be the same. In the context

524
00:30:44,480 --> 00:30:48,400
Speaker 4: of hetero couples, Husbands who adore their wives tend to

525
00:30:48,400 --> 00:30:51,320
Speaker 4: be lifted up as wife guys in the same way

526
00:30:51,320 --> 00:30:54,760
Speaker 4: that they're more easily rewarded socially for being an active

527
00:30:54,840 --> 00:30:58,080
Speaker 4: part of their children's lives. And while there's intersecting issues

528
00:30:58,120 --> 00:31:01,360
Speaker 4: that caused people to project on to Coffee Wife, I

529
00:31:01,400 --> 00:31:04,280
Speaker 4: still think this boils down to an Internet classic. Women

530
00:31:04,320 --> 00:31:07,960
Speaker 4: are fair game for just about anything. There's no social

531
00:31:08,040 --> 00:31:11,680
Speaker 4: incentive for Daisy to say she loves her husband, because

532
00:31:11,720 --> 00:31:15,120
Speaker 4: when a woman adores spending time with her husband, So what,

533
00:31:15,680 --> 00:31:17,840
Speaker 4: it would be selfish of her to not love spending

534
00:31:17,880 --> 00:31:20,280
Speaker 4: time with him. When a woman takes good care of

535
00:31:20,360 --> 00:31:24,800
Speaker 4: and loves her children, so what, that's the natural expectation,

536
00:31:25,280 --> 00:31:27,800
Speaker 4: And coming up short in either department is still met

537
00:31:27,840 --> 00:31:31,800
Speaker 4: with easier, more reflexive criticism, even with gains made in

538
00:31:31,920 --> 00:31:35,360
Speaker 4: general gender perception. But while I do firmly believe that

539
00:31:35,440 --> 00:31:39,520
Speaker 4: Daisy was dragged online for simply being happy, I want

540
00:31:39,560 --> 00:31:42,400
Speaker 4: to state the obvious and say, of course women can

541
00:31:42,440 --> 00:31:45,560
Speaker 4: fucking suck online. There's plenty of precedent for that, because

542
00:31:45,600 --> 00:31:49,520
Speaker 4: women are people, and there are clear patterns en mass

543
00:31:49,520 --> 00:31:53,680
Speaker 4: and as individuals for assists white women specifically like Daisy

544
00:31:53,760 --> 00:31:58,080
Speaker 4: and myself, to behave in an insensitive at best, bigoted

545
00:31:58,120 --> 00:32:01,520
Speaker 4: and benefiting from the whiteness that patriarch and capitalism rewards,

546
00:32:01,520 --> 00:32:03,520
Speaker 4: and being generally a condescending piece of shit to people

547
00:32:03,520 --> 00:32:06,880
Speaker 4: who are more marginalized than themselves. That's a lot of

548
00:32:06,880 --> 00:32:10,360
Speaker 4: words to say a no longer trendy term that is

549
00:32:10,400 --> 00:32:14,560
Speaker 4: still somewhat useful, and it is girl boss. There's a

550
00:32:14,560 --> 00:32:17,520
Speaker 4: bunch of conflicting definitions of this term. Some are as

551
00:32:17,520 --> 00:32:21,160
Speaker 4: simple as quote a woman, especially a young woman who

552
00:32:21,200 --> 00:32:24,880
Speaker 4: is ambitious and successful in her career. Unquote and others

553
00:32:24,960 --> 00:32:27,200
Speaker 4: as I think of the girl boss are connected more

554
00:32:27,240 --> 00:32:31,040
Speaker 4: closely to women using the language of feminism to accrue

555
00:32:31,080 --> 00:32:35,400
Speaker 4: power while actively upholding the status quo. Probably the most

556
00:32:35,400 --> 00:32:38,320
Speaker 4: famous example of this is Sheryl Sandberg, who wrote the

557
00:32:38,320 --> 00:32:41,560
Speaker 4: bestseller Lean In in twenty thirteen to encourage women to

558
00:32:41,600 --> 00:32:45,680
Speaker 4: advocate for themselves in the workplace. She is the ultimate

559
00:32:45,760 --> 00:32:49,320
Speaker 4: girl boss to me for a few reasons. First of all,

560
00:32:49,480 --> 00:32:53,400
Speaker 4: she is a huge beneficiary of capitalism that is actively harmful.

561
00:32:53,680 --> 00:32:57,120
Speaker 4: She was the COO of Facebook during years and years

562
00:32:57,160 --> 00:33:00,560
Speaker 4: of infinite growth. And second of all, she's using her

563
00:33:00,560 --> 00:33:04,160
Speaker 4: position as a powerful woman to sell you something. And

564
00:33:04,200 --> 00:33:06,720
Speaker 4: that something is that the only thing holding you back

565
00:33:06,800 --> 00:33:09,080
Speaker 4: as a woman in the workplace is not the system

566
00:33:09,120 --> 00:33:12,600
Speaker 4: you find yourself in, but something you are neglecting to

567
00:33:12,720 --> 00:33:15,760
Speaker 4: do it self. Helps snake oil that bullies the women

568
00:33:15,800 --> 00:33:19,120
Speaker 4: who are reading it. Here's a quote. I'm sorry if

569
00:33:19,120 --> 00:33:21,800
Speaker 4: this sounds harsh or surprises anyone, but this is where

570
00:33:21,800 --> 00:33:23,959
Speaker 4: we are. If you want the outcome to be different,

571
00:33:24,240 --> 00:33:28,080
Speaker 4: you will have to do something about it. Oh it's

572
00:33:28,200 --> 00:33:31,600
Speaker 4: your fault. She also says this we need to stop

573
00:33:31,640 --> 00:33:35,000
Speaker 4: telling women get a mentor and you will excel. Instead,

574
00:33:35,040 --> 00:33:37,600
Speaker 4: we need to tell them excel and you will get

575
00:33:37,600 --> 00:33:44,719
Speaker 4: a mentor. Oh, it's my fault. Twenty dollars well spent, thanks, Cheryl.

576
00:33:45,000 --> 00:33:47,760
Speaker 4: That's the kind of girl boss shit we're talking about.

577
00:33:48,160 --> 00:33:52,960
Speaker 4: So a very instructive term that is often misused after

578
00:33:53,040 --> 00:33:58,120
Speaker 4: being sucked into this linguistic, misogynist vortex. The difficulty with

579
00:33:58,320 --> 00:34:01,120
Speaker 4: the girl boss tag gets to why I think Coffee

580
00:34:01,160 --> 00:34:04,280
Speaker 4: wife was done so dirty. There are people who aren't

581
00:34:04,280 --> 00:34:07,600
Speaker 4: big fans of women who glommed onto this word to

582
00:34:07,760 --> 00:34:11,799
Speaker 4: use it interchangeably with all women or women who had

583
00:34:11,840 --> 00:34:14,840
Speaker 4: any power over them at work. If your manager is

584
00:34:14,880 --> 00:34:18,000
Speaker 4: a woman, that doesn't mean she is cynically using tools

585
00:34:18,000 --> 00:34:21,120
Speaker 4: of the patriarchy to oppress you while assuring other women

586
00:34:21,360 --> 00:34:25,000
Speaker 4: they're doing something wrong in order to personally profit. It's

587
00:34:25,000 --> 00:34:28,640
Speaker 4: a very specific set of behaviors, and being a girl

588
00:34:28,719 --> 00:34:32,080
Speaker 4: boss doesn't mean the women in question haven't experienced gender

589
00:34:32,120 --> 00:34:36,480
Speaker 4: discrimination themselves. In fact, I'd wager that all of them have.

590
00:34:37,320 --> 00:34:40,960
Speaker 4: This simply does not describe a woo woo twenty four

591
00:34:41,000 --> 00:34:44,320
Speaker 4: year old drinking coffee in the garden. The anger is valid,

592
00:34:44,600 --> 00:34:48,080
Speaker 4: but it is misplaced. Daisy wasn't trying to make money

593
00:34:48,120 --> 00:34:51,200
Speaker 4: by saying this. She wasn't aiming to change minds or

594
00:34:51,280 --> 00:34:54,680
Speaker 4: hurt anyone, or, according to her, even reach outside of

595
00:34:54,680 --> 00:34:59,480
Speaker 4: her normal audience. She was just sharing something you know,

596
00:35:00,239 --> 00:35:03,120
Speaker 4: like we're told, is the whole point of social media,

597
00:35:03,280 --> 00:35:05,680
Speaker 4: And given the state of Twitter in the fall of

598
00:35:05,719 --> 00:35:10,160
Speaker 4: twenty twenty two and on this specific week, the algorithm

599
00:35:10,200 --> 00:35:13,720
Speaker 4: pushing this high engagement story makes a lot of sense.

600
00:35:14,440 --> 00:35:17,120
Speaker 4: There were a number of algorithmic shifts on Twitter and

601
00:35:17,200 --> 00:35:20,040
Speaker 4: in social media writ large in this year. If you're

602
00:35:20,080 --> 00:35:23,040
Speaker 4: a Twitter user yourself or I'm not going to say X,

603
00:35:23,080 --> 00:35:25,880
Speaker 4: please don't contact me about this. If you're a Twitter

604
00:35:25,960 --> 00:35:30,400
Speaker 4: user yourself or a proud Twitter retiree, you might remember

605
00:35:30,560 --> 00:35:35,160
Speaker 4: when their timeline became completely algorithmically driven instead of what

606
00:35:35,239 --> 00:35:37,560
Speaker 4: it had been for years and years, which was a

607
00:35:37,600 --> 00:35:41,200
Speaker 4: real time feed of people you had chosen to follow. Now,

608
00:35:41,360 --> 00:35:43,919
Speaker 4: people you didn't follow would be sorted to the top

609
00:35:43,960 --> 00:35:46,359
Speaker 4: of your feed if the algorithm thought you were likely

610
00:35:46,400 --> 00:35:49,120
Speaker 4: to interact with the post based on what you'd interacted

611
00:35:49,160 --> 00:35:52,200
Speaker 4: with in the past, and the people you actually chose

612
00:35:52,239 --> 00:35:56,040
Speaker 4: to follow might see their content get pushed further and

613
00:35:56,160 --> 00:36:00,200
Speaker 4: further down. Users got really pissed off about this, and

614
00:36:00,239 --> 00:36:03,480
Speaker 4: Twitter tried to mitigate the issue by splitting everything into

615
00:36:03,560 --> 00:36:07,080
Speaker 4: two feeds. So if you opened the website on your laptop,

616
00:36:07,320 --> 00:36:10,719
Speaker 4: it would default the new shitty algorithm feed and you

617
00:36:10,760 --> 00:36:14,440
Speaker 4: could shift over to the timeline you'd had for fifteen years.

618
00:36:14,719 --> 00:36:17,239
Speaker 4: But it would take some effort, and it's posts like

619
00:36:17,360 --> 00:36:21,920
Speaker 4: daisies that would get sorted into this new algorithmically driven feed,

620
00:36:22,239 --> 00:36:24,600
Speaker 4: the one you didn't ask for and the one that

621
00:36:24,760 --> 00:36:28,959
Speaker 4: no one is prepared to be sorted into. And within

622
00:36:29,000 --> 00:36:32,200
Speaker 4: a week of the Coffee Wife flare up, a looming

623
00:36:32,280 --> 00:36:38,239
Speaker 4: Twitter acquisition was finally completed. After months of legal wrangling

624
00:36:38,440 --> 00:36:43,040
Speaker 4: and negotiation, Elon Musk has finally bought social media company Twitter.

625
00:36:43,640 --> 00:36:46,759
Speaker 4: Earlier in twenty twenty two, Elon Musk, who I think

626
00:36:46,800 --> 00:36:50,080
Speaker 4: we can all agree only had the best intentions and

627
00:36:50,200 --> 00:36:53,440
Speaker 4: deserves the benefit of the doubt, offered to buy Twitter

628
00:36:53,480 --> 00:36:56,200
Speaker 4: on a whim for fifty four dollars and twenty cents

629
00:36:56,200 --> 00:36:59,320
Speaker 4: a share, just months after he'd become the company's largest

630
00:36:59,320 --> 00:37:02,759
Speaker 4: shareholder at nearly ten percent. This put the prospective deal

631
00:37:03,000 --> 00:37:07,080
Speaker 4: at forty four billion dollars and Twitter accepted the offer

632
00:37:07,680 --> 00:37:10,680
Speaker 4: very quickly. They genuinely didn't seem to think he'd go

633
00:37:10,760 --> 00:37:13,279
Speaker 4: through with it, and accepted to all but resist a

634
00:37:13,360 --> 00:37:17,200
Speaker 4: hostile takeover from Musk. But Musk, determined to pivot the

635
00:37:17,239 --> 00:37:21,560
Speaker 4: platform to white supremacy, doubled down, declaring that his ownership

636
00:37:21,560 --> 00:37:26,040
Speaker 4: would mean less bots and more free speech. He certainly

637
00:37:26,080 --> 00:37:28,960
Speaker 4: made good on the former in the fascist content is

638
00:37:29,120 --> 00:37:32,680
Speaker 4: king sense, but the crackdown on bots is pretty hilarious

639
00:37:32,719 --> 00:37:35,720
Speaker 4: for a site that I can't even pay to stop

640
00:37:35,760 --> 00:37:39,680
Speaker 4: auto posting my pussy and bio underneath pictures of me

641
00:37:39,800 --> 00:37:43,000
Speaker 4: and my infant nephew. So yeah, this change of ownership

642
00:37:43,239 --> 00:37:46,799
Speaker 4: was famously a disaster. Elon Musk tried to back out

643
00:37:46,880 --> 00:37:50,480
Speaker 4: of the objectively bad deal that was his idea in July,

644
00:37:50,880 --> 00:37:53,520
Speaker 4: but was unable to and was all but forced to

645
00:37:53,560 --> 00:37:56,040
Speaker 4: go through with the deal less than a week after.

646
00:37:56,200 --> 00:38:00,319
Speaker 4: Daisy was declared the Coffee Wife, and what happened after

647
00:38:00,360 --> 00:38:03,239
Speaker 4: that was well, it's why Twitter has been in sharp

648
00:38:03,280 --> 00:38:07,000
Speaker 4: decline ever since. Just a small sampler platter of incidents

649
00:38:07,040 --> 00:38:14,720
Speaker 4: since this time, welcoming Donald Trump, Kanye and Alex Jones

650
00:38:14,760 --> 00:38:19,000
Speaker 4: back to Twitter and generally promoting fascists challenging Mark Zuckerberg

651
00:38:19,040 --> 00:38:21,960
Speaker 4: to a cage match and tanking the company's net worth

652
00:38:22,160 --> 00:38:28,560
Speaker 4: by over fifty percent. There's a very depressing lens that

653
00:38:28,560 --> 00:38:31,799
Speaker 4: we can see the coffee wife incident through as this

654
00:38:32,160 --> 00:38:36,800
Speaker 4: dying gasp of old school misogyny on Twitter, moments before

655
00:38:36,840 --> 00:38:52,960
Speaker 4: it was about to get much, much, much worse. And

656
00:38:53,080 --> 00:38:56,200
Speaker 4: how bad hasn't gotten on the Internet since twenty twenty two.

657
00:38:56,880 --> 00:38:59,920
Speaker 4: I went to an expert, my pal, Bridget Todd, host

658
00:39:00,040 --> 00:39:03,800
Speaker 4: of the incredible podcast there Are No Girls on the Internet.

659
00:39:04,280 --> 00:39:07,719
Speaker 1: Here's our chat. My name is Bridget Todd. I'm the

660
00:39:07,760 --> 00:39:11,160
Speaker 1: host and creator of Iheartradios tech and culture podcast There

661
00:39:11,160 --> 00:39:13,480
Speaker 1: Are No Girls on the Internet, And I guess you

662
00:39:13,520 --> 00:39:19,200
Speaker 1: could say I'm a tech Internet enthusiast, aficionado, whatever you

663
00:39:19,239 --> 00:39:19,800
Speaker 1: want to say.

664
00:39:20,000 --> 00:39:22,920
Speaker 4: I'm excited to talk coffee wife with you. Why do

665
00:39:22,960 --> 00:39:25,720
Speaker 4: you think that people had such a strong emotional reaction

666
00:39:25,960 --> 00:39:27,320
Speaker 4: to coffee Wife.

667
00:39:27,880 --> 00:39:31,319
Speaker 1: Well, one, I think it's absolutely algorithmic, right. I think

668
00:39:31,360 --> 00:39:34,440
Speaker 1: that we know a lot about how algorithms work. I

669
00:39:34,440 --> 00:39:37,200
Speaker 1: think that they absolutely are feeding us and pushing us

670
00:39:37,239 --> 00:39:42,160
Speaker 1: content that is going to elicit strong reactions, emotional reactions

671
00:39:42,160 --> 00:39:43,960
Speaker 1: from us. So even if you don't know this woman.

672
00:39:44,040 --> 00:39:46,520
Speaker 1: Don't follow this woman. She wasn't like somebody who had

673
00:39:46,680 --> 00:39:49,120
Speaker 1: a ton of followers. She had a relatively small account.

674
00:39:49,440 --> 00:39:53,320
Speaker 1: Platforms know this is content that it's eliciting strong reaction,

675
00:39:53,520 --> 00:39:56,480
Speaker 1: strong engagement. Let's make sure that more people see it,

676
00:39:56,719 --> 00:39:59,560
Speaker 1: you know, that's the name of the game for platforms. However,

677
00:40:00,160 --> 00:40:03,080
Speaker 1: I do think that the timeframe kind of matters, Like

678
00:40:03,520 --> 00:40:06,279
Speaker 1: I think that this was a time where do you

679
00:40:06,320 --> 00:40:09,839
Speaker 1: remember how in the very beginning of the pandemic we

680
00:40:09,840 --> 00:40:11,759
Speaker 1: were all there was a sort of novelty to it

681
00:40:11,800 --> 00:40:14,560
Speaker 1: where it was like who knows what's happening? But then

682
00:40:14,719 --> 00:40:16,440
Speaker 1: that kind of were off, and then it was like, well,

683
00:40:16,480 --> 00:40:18,120
Speaker 1: I guess this is just all of our lives now.

684
00:40:18,440 --> 00:40:21,080
Speaker 1: And I think that this happened at a time when

685
00:40:21,120 --> 00:40:23,400
Speaker 1: a lot of people were just sort of grappling with that.

686
00:40:23,480 --> 00:40:25,960
Speaker 1: I think for me personally, it was a time where

687
00:40:25,960 --> 00:40:28,279
Speaker 1: I was spending way more time than I should have

688
00:40:28,320 --> 00:40:32,120
Speaker 1: been on screens on the internet, really paying a lot

689
00:40:32,160 --> 00:40:34,439
Speaker 1: of attention to what strangers on the Internet were doing,

690
00:40:34,600 --> 00:40:36,799
Speaker 1: because I didn't have a lot going on outside of that, right,

691
00:40:36,800 --> 00:40:38,120
Speaker 1: I wasn't going out the way I used to.

692
00:40:38,280 --> 00:40:39,920
Speaker 2: All of that, and I also.

693
00:40:39,719 --> 00:40:44,920
Speaker 1: Think we were all feeling the sort of like existential.

694
00:40:44,600 --> 00:40:47,759
Speaker 2: Dread of how reality feels right now.

695
00:40:47,840 --> 00:40:51,520
Speaker 1: Right Everything is expensive, rents are rising, Inflation is terrible.

696
00:40:51,960 --> 00:40:53,920
Speaker 1: It just feels like we are being squeezed from so

697
00:40:54,000 --> 00:40:55,000
Speaker 1: many different angles.

698
00:40:55,200 --> 00:40:57,000
Speaker 2: And so when somebody comes along.

699
00:40:56,800 --> 00:41:01,000
Speaker 1: With just pure Joel, the pure Joel of a you know,

700
00:41:01,200 --> 00:41:03,759
Speaker 1: having coffee in their garden with their husband every morning,

701
00:41:03,840 --> 00:41:06,760
Speaker 1: and you know, isn't this nice, It's like a trigger

702
00:41:07,000 --> 00:41:09,400
Speaker 1: that It's not surprising to me that it was this

703
00:41:09,880 --> 00:41:11,480
Speaker 1: big tension point for so many people.

704
00:41:12,000 --> 00:41:14,440
Speaker 4: That's so interesting. I think of all the conversations I've

705
00:41:14,480 --> 00:41:16,640
Speaker 4: been having, I'd be curious what you think about that,

706
00:41:16,719 --> 00:41:20,440
Speaker 4: of like how the pandemic sort of warped our relationship

707
00:41:20,440 --> 00:41:24,520
Speaker 4: to the Internet and what it looks like trying to

708
00:41:24,560 --> 00:41:29,360
Speaker 4: sort of return to straddling real life and Internet life.

709
00:41:29,520 --> 00:41:34,400
Speaker 1: Yeah, boy, do I identify with that and feel you on that.

710
00:41:34,880 --> 00:41:37,880
Speaker 1: I mean, I can speak for myself. I am not

711
00:41:38,000 --> 00:41:41,759
Speaker 1: proud of what the pandemic, how I responded to the

712
00:41:41,760 --> 00:41:45,640
Speaker 1: pandemic socially, right, I also am a pretty socially anxious person.

713
00:41:45,680 --> 00:41:46,520
Speaker 2: I'm somebody who's in.

714
00:41:46,480 --> 00:41:50,600
Speaker 1: My head a lot, and I'm not proud to say this,

715
00:41:50,840 --> 00:41:52,480
Speaker 1: but I would bet that I'm not the only person

716
00:41:52,560 --> 00:41:55,480
Speaker 1: who feels this way. I think during the pandemic, you know,

717
00:41:55,520 --> 00:41:58,399
Speaker 1: we were watching people die, we were watching people lose

718
00:41:58,440 --> 00:42:01,120
Speaker 1: loved ones, we were watching people lose their livelihoods. It

719
00:42:01,200 --> 00:42:03,640
Speaker 1: was a really tough time, and so it was hard

720
00:42:04,440 --> 00:42:08,000
Speaker 1: for me as somebody who luckily was very privileged, and

721
00:42:08,040 --> 00:42:09,799
Speaker 1: that that wasn't the case for me, right, Like I

722
00:42:09,840 --> 00:42:12,719
Speaker 1: got COVID. People I know got COVID, but thankfully I

723
00:42:12,719 --> 00:42:15,480
Speaker 1: didn't lose my loved ones. It wasn't impacting me the

724
00:42:15,480 --> 00:42:17,440
Speaker 1: way that it was. I'm not an essential worker, right,

725
00:42:17,480 --> 00:42:21,600
Speaker 1: and so I think that for me personally, it was.

726
00:42:23,080 --> 00:42:24,480
Speaker 2: Strange, too deep.

727
00:42:24,280 --> 00:42:27,719
Speaker 1: To grapple with that, this feeling of like I am

728
00:42:27,719 --> 00:42:30,440
Speaker 1: going through a tough time and so is everyone. I

729
00:42:30,480 --> 00:42:34,319
Speaker 1: think it for me created this dynamic where I hate

730
00:42:34,320 --> 00:42:35,840
Speaker 1: to say it, but I was very much like what

731
00:42:35,920 --> 00:42:39,000
Speaker 1: about my pain? You know, Like why is no like

732
00:42:39,120 --> 00:42:40,880
Speaker 1: when is it going to be my turn for somebody

733
00:42:40,920 --> 00:42:43,920
Speaker 1: to see me? Like I wasn't an essential worker. Nobody

734
00:42:43,960 --> 00:42:45,680
Speaker 1: around me died, but I still had a tough time.

735
00:42:46,000 --> 00:42:50,280
Speaker 1: I was finding myself in this like almost very narcissistic

736
00:42:50,440 --> 00:42:54,479
Speaker 1: place of wanting somebody to acknowledge what I had been through,

737
00:42:54,520 --> 00:42:56,759
Speaker 1: and so I think with Coffee Lady, I think it

738
00:42:56,800 --> 00:43:02,120
Speaker 1: was a lot of people who perhaps were wanting someone

739
00:43:02,160 --> 00:43:05,319
Speaker 1: to see their pain, wanting others to acknowledge their pain

740
00:43:05,440 --> 00:43:08,279
Speaker 1: and their anxiety and their loneliness and their frustration, which

741
00:43:08,320 --> 00:43:10,920
Speaker 1: is something that I can relate to really deeply, and

742
00:43:10,960 --> 00:43:13,799
Speaker 1: so I think that's part of why, because some of

743
00:43:13,840 --> 00:43:17,040
Speaker 1: the replies that she got would be like, I can't afford.

744
00:43:16,760 --> 00:43:18,480
Speaker 2: A garden, I don't have a husband.

745
00:43:18,840 --> 00:43:20,839
Speaker 1: You know, I'm alone here, I don't have any friends,

746
00:43:20,880 --> 00:43:25,520
Speaker 1: Like people really making it about themselves and what they lack,

747
00:43:25,640 --> 00:43:28,920
Speaker 1: and like something about that tweet I think highlighted the

748
00:43:29,040 --> 00:43:32,040
Speaker 1: lack that a lot of people were feeling. And I

749
00:43:32,360 --> 00:43:35,160
Speaker 1: just I really, it's easy to dunk on these people

750
00:43:35,160 --> 00:43:38,040
Speaker 1: and be like, Wow, you're so disregulated that that's that

751
00:43:38,080 --> 00:43:40,200
Speaker 1: this woman, this random woman's tweet is making you feel

752
00:43:40,200 --> 00:43:40,600
Speaker 1: that way.

753
00:43:40,760 --> 00:43:42,040
Speaker 2: But I also kind of get it.

754
00:43:42,160 --> 00:43:44,359
Speaker 4: You're totally right. And I know I've been guilty of

755
00:43:44,400 --> 00:43:48,120
Speaker 4: this in the past, and probably during the pandemic era Internet,

756
00:43:48,160 --> 00:43:53,080
Speaker 4: where you're taking like your personal pain, and I've had

757
00:43:53,120 --> 00:43:54,680
Speaker 4: moments where I'm like, I don't want to see someone

758
00:43:54,680 --> 00:43:57,640
Speaker 4: happy right now because I'm not. And like, I think

759
00:43:57,680 --> 00:43:59,319
Speaker 4: that there's a lot of that, but some of it

760
00:43:59,400 --> 00:44:02,880
Speaker 4: is sort of manager infesting as a political statement. I

761
00:44:02,880 --> 00:44:05,640
Speaker 4: can't quite get my head around that phenomenon because I

762
00:44:05,640 --> 00:44:09,840
Speaker 4: don't want to discount the fact that like class rage

763
00:44:09,840 --> 00:44:13,680
Speaker 4: and class anxiety online. I mean, it makes total sense.

764
00:44:13,760 --> 00:44:17,719
Speaker 4: I experienced it a lot, especially it's sort of the

765
00:44:17,760 --> 00:44:21,960
Speaker 4: further back you go, but she's so clearly not the

766
00:44:22,040 --> 00:44:25,000
Speaker 4: person that can. I think it's interesting online when people

767
00:44:25,080 --> 00:44:28,279
Speaker 4: dogpile on someone who cannot help them, right.

768
00:44:28,920 --> 00:44:31,920
Speaker 1: I do think there's a gendered aspect to it. I

769
00:44:31,920 --> 00:44:34,719
Speaker 1: haven't really kind of grappled with this too much just yet,

770
00:44:34,719 --> 00:44:38,080
Speaker 1: but like I know, for me, when I'm scrolling TikTok

771
00:44:38,200 --> 00:44:42,239
Speaker 1: or Instagram, there is something about the visualization of a

772
00:44:42,280 --> 00:44:44,879
Speaker 1: woman who seems like she's got her shit together, She's

773
00:44:44,880 --> 00:44:48,000
Speaker 1: got it all figured out, she wears the perfect two piece,

774
00:44:48,440 --> 00:44:51,920
Speaker 1: you know, workouts that she eats right, she starts her

775
00:44:52,000 --> 00:44:54,920
Speaker 1: day with like lemon water or macha instead of coffee whatever.

776
00:44:54,960 --> 00:44:59,320
Speaker 4: It is, three gorgeous children who are wealthy sat Yeah, exactly.

777
00:45:00,000 --> 00:45:03,840
Speaker 1: I think that coffee Lady's tweet at least for me,

778
00:45:04,480 --> 00:45:11,200
Speaker 1: triggered a kind of very gendered, almost like politicized anxiety

779
00:45:11,239 --> 00:45:12,960
Speaker 1: that there are women out there who are doing it

780
00:45:13,080 --> 00:45:15,600
Speaker 1: right and bridget you are doing it wrong, like something

781
00:45:15,600 --> 00:45:17,919
Speaker 1: about like like there has never been a day where

782
00:45:17,920 --> 00:45:19,200
Speaker 1: I'm able to start my day.

783
00:45:20,520 --> 00:45:22,800
Speaker 2: Serenely drinking coffee in my garden.

784
00:45:22,840 --> 00:45:24,759
Speaker 1: I actually do have a small garden, and I never

785
00:45:24,800 --> 00:45:27,200
Speaker 1: start my day out there because I start my day

786
00:45:27,239 --> 00:45:30,600
Speaker 1: like most people, like frazzled late for a call, just

787
00:45:30,640 --> 00:45:33,759
Speaker 1: trying to chug some coffee while I'm getting dressed, like.

788
00:45:33,920 --> 00:45:35,040
Speaker 2: Doing a million other things.

789
00:45:35,280 --> 00:45:40,400
Speaker 1: Sure I shouldn't be taking a moment smelling the flowers, journaling, YadA, YadA, YadA.

790
00:45:40,200 --> 00:45:42,280
Speaker 4: But yes, gratitude journal exactly.

791
00:45:42,360 --> 00:45:45,160
Speaker 2: But who does that right? And so I think there

792
00:45:45,280 --> 00:45:47,279
Speaker 2: is something where women.

793
00:45:47,040 --> 00:45:49,600
Speaker 1: Are told that you have to in order to sort

794
00:45:49,600 --> 00:45:52,040
Speaker 1: of signal that you have it together, your mornings have

795
00:45:52,080 --> 00:45:54,040
Speaker 1: to look like X y Z. And I think that

796
00:45:54,400 --> 00:45:58,840
Speaker 1: something about coffee Lady, something about that tweet signaled to

797
00:45:58,920 --> 00:46:02,000
Speaker 1: women like I've got it all together? Do you feel

798
00:46:02,080 --> 00:46:04,000
Speaker 1: like crap that you don't. I don't think she was.

799
00:46:04,320 --> 00:46:06,319
Speaker 1: I certainly don't think she was trying to do that.

800
00:46:06,440 --> 00:46:08,360
Speaker 1: But that's I think that's probably how it hit some

801
00:46:08,440 --> 00:46:08,759
Speaker 1: of us.

802
00:46:09,040 --> 00:46:10,799
Speaker 4: The Internet, I think, like a lot of things is

803
00:46:10,840 --> 00:46:14,279
Speaker 4: sort of built to make women angry at each other

804
00:46:14,880 --> 00:46:18,360
Speaker 4: and present each other. And yeah, I mean, could you

805
00:46:18,400 --> 00:46:19,959
Speaker 4: speak to that a little bit. I know that that's

806
00:46:20,280 --> 00:46:20,800
Speaker 4: your beat.

807
00:46:21,239 --> 00:46:25,600
Speaker 1: Yes, I mean, it's just a document, a well documented fact.

808
00:46:26,160 --> 00:46:30,080
Speaker 1: Algorithms want women to feel like shit. They want women

809
00:46:30,120 --> 00:46:32,799
Speaker 1: to be comparing themselves to other women, they want women

810
00:46:32,840 --> 00:46:35,000
Speaker 1: to be feeling bad. They want women to be feeling

811
00:46:35,080 --> 00:46:38,279
Speaker 1: like crap all the time. And algorithms and platforms and

812
00:46:38,320 --> 00:46:41,480
Speaker 1: tech leaders make money off of women feeling.

813
00:46:41,160 --> 00:46:43,200
Speaker 2: Like shit about themselves. That's just a fact, right.

814
00:46:43,239 --> 00:46:46,600
Speaker 1: And so if you've ever been scrolling Instagram or TikTok

815
00:46:46,680 --> 00:46:49,520
Speaker 1: or whatever and you keep being surfaced content that makes

816
00:46:49,560 --> 00:46:52,560
Speaker 1: you feel like crap, that's not you. You're not crazy

817
00:46:52,640 --> 00:46:56,680
Speaker 1: or sensitive. Algorithms and platforms do that with intention because

818
00:46:56,719 --> 00:46:58,799
Speaker 1: it keeps you on the platform longer, it keeps you

819
00:46:58,840 --> 00:47:00,719
Speaker 1: coming back, and it makes them money. It is a

820
00:47:00,880 --> 00:47:04,759
Speaker 1: very twisted dynamic that we are a cog in this

821
00:47:04,880 --> 00:47:08,959
Speaker 1: cycle that is making other people, mostly men, rich off

822
00:47:08,960 --> 00:47:12,239
Speaker 1: of our anxiety, off of our fears, off of us

823
00:47:12,320 --> 00:47:15,319
Speaker 1: being in competition with each other and rather than like

824
00:47:15,640 --> 00:47:18,439
Speaker 1: celebrating the ways that we are different, celebrating the ways

825
00:47:18,440 --> 00:47:20,560
Speaker 1: in which like, oh well, like my brand is this,

826
00:47:20,800 --> 00:47:23,640
Speaker 1: I'm a hot mess, I own it whatever. Whatever, algorithms

827
00:47:23,680 --> 00:47:26,000
Speaker 1: trick us into thinking that all of these great things

828
00:47:26,000 --> 00:47:28,839
Speaker 1: that make us who we are are actually foibles, are

829
00:47:28,880 --> 00:47:32,640
Speaker 1: actually bad And yeah, I mean there's been study after

830
00:47:32,719 --> 00:47:35,799
Speaker 1: study that shows that the more time you spend on

831
00:47:35,880 --> 00:47:39,680
Speaker 1: particularly Instagram, the more young women feel bad about themselves,

832
00:47:39,680 --> 00:47:42,160
Speaker 1: the more body anxiety they have, the more likely they

833
00:47:42,160 --> 00:47:45,200
Speaker 1: are to engage in things like food issues or disordered eating.

834
00:47:45,520 --> 00:47:47,920
Speaker 1: And none of that is by mistake and it's all

835
00:47:47,960 --> 00:47:50,040
Speaker 1: by design. It is a feature, not a bug.

836
00:47:51,360 --> 00:47:55,720
Speaker 4: And that would also apply to coffee life. That people

837
00:47:55,760 --> 00:47:58,160
Speaker 4: were attacking her as if she was like the root

838
00:47:58,280 --> 00:48:00,839
Speaker 4: cause of it. It was very strange. I forget who

839
00:48:00,880 --> 00:48:04,160
Speaker 4: I was talking to the other day about how they

840
00:48:04,160 --> 00:48:07,360
Speaker 4: felt like they had fucked up their algorithm because they

841
00:48:07,440 --> 00:48:11,320
Speaker 4: said that they weren't interested in something and the algorithm

842
00:48:11,360 --> 00:48:14,000
Speaker 4: kept serving that to them because they cared enough to

843
00:48:14,080 --> 00:48:17,000
Speaker 4: say I'm not interested. And the only way to truly

844
00:48:18,200 --> 00:48:21,800
Speaker 4: demonstrate you're not interested is to keep scrolling and don't stop.

845
00:48:21,960 --> 00:48:24,880
Speaker 4: But like, if you are. If you theoretically, you know,

846
00:48:25,040 --> 00:48:28,600
Speaker 4: see like a coffee wife TikTok come up and you

847
00:48:28,680 --> 00:48:32,719
Speaker 4: care enough to say I don't like this, the algorithm

848
00:48:32,840 --> 00:48:34,399
Speaker 4: will serve it to you again. And so I ran

849
00:48:34,480 --> 00:48:39,120
Speaker 4: an experiment and it's completely true, like that the kind

850
00:48:39,120 --> 00:48:41,040
Speaker 4: of content I went out of my way to say

851
00:48:41,120 --> 00:48:44,440
Speaker 4: I don't like this. The algorithm responds by being like, well,

852
00:48:44,480 --> 00:48:47,560
Speaker 4: maybe you'll interact with it negatively because it makes you

853
00:48:47,600 --> 00:48:48,120
Speaker 4: feel bad.

854
00:48:48,520 --> 00:48:53,120
Speaker 1: Yes, And so it's so I've experienced the exact same thing.

855
00:48:53,200 --> 00:48:56,040
Speaker 1: I completely agree with you, And imagine how harmful that

856
00:48:56,200 --> 00:48:59,520
Speaker 1: is when it's content that you find triggering. Right, when

857
00:48:59,520 --> 00:49:01,719
Speaker 1: it's content that you have identified like that might not

858
00:49:01,760 --> 00:49:04,000
Speaker 1: be safe or healthy for me to see and engage with.

859
00:49:04,120 --> 00:49:06,799
Speaker 1: Right if the algorithm has has gleamed like, oh, she

860
00:49:06,880 --> 00:49:08,800
Speaker 1: has a little bit of an issue with X y Z.

861
00:49:09,840 --> 00:49:11,960
Speaker 1: Let's get showing it to her and see what happens.

862
00:49:12,480 --> 00:49:13,640
Speaker 2: Yeah, really that cool.

863
00:49:14,200 --> 00:49:18,400
Speaker 4: The part that's hard is even when I'm looking for it,

864
00:49:18,400 --> 00:49:23,120
Speaker 4: it's hard to escape the like emotional experience of I

865
00:49:23,120 --> 00:49:26,200
Speaker 4: don't want to see that, and like feeling that your

866
00:49:26,239 --> 00:49:29,400
Speaker 4: anger for whatever reason, does seem it routes at the

867
00:49:29,440 --> 00:49:33,799
Speaker 4: person because you can't you know the real kind of Yeah,

868
00:49:33,840 --> 00:49:37,200
Speaker 4: this suendse conspiratorial, but like the real enemy has no face, right,

869
00:49:37,280 --> 00:49:39,320
Speaker 4: And so I feel like there is this sort of

870
00:49:39,400 --> 00:49:43,239
Speaker 4: very human instinct to try to place a face and

871
00:49:43,280 --> 00:49:47,360
Speaker 4: a name to what is bothering you, when in reality

872
00:49:47,800 --> 00:49:51,680
Speaker 4: it is something much larger, like you know, social media

873
00:49:51,719 --> 00:49:55,520
Speaker 4: algorithms that are trying to make you upset, like the

874
00:49:55,600 --> 00:50:00,359
Speaker 4: concept of class, and like these huge things. And it's

875
00:50:00,600 --> 00:50:03,399
Speaker 4: finding a sort of villain of the day to take

876
00:50:03,440 --> 00:50:07,720
Speaker 4: it out on, even when that person sucks. In this case,

877
00:50:07,800 --> 00:50:10,240
Speaker 4: they didn't, but sometimes they do, but it still doesn't

878
00:50:10,320 --> 00:50:11,600
Speaker 4: It's so unproductive.

879
00:50:12,320 --> 00:50:16,319
Speaker 1: Yeah, we are making a bunch of random people proxies

880
00:50:16,360 --> 00:50:19,000
Speaker 1: for a lot of our very valid anger and pain

881
00:50:19,080 --> 00:50:22,160
Speaker 1: and fear. That's why I always say, like we're it's

882
00:50:22,200 --> 00:50:24,520
Speaker 1: a game and we're all being played. The only winner

883
00:50:24,560 --> 00:50:27,080
Speaker 1: here are tech platforms and people who run them and

884
00:50:27,080 --> 00:50:29,319
Speaker 1: people who make money from them. And so even if

885
00:50:29,320 --> 00:50:32,200
Speaker 1: you are running a successful little grift for a while,

886
00:50:32,480 --> 00:50:35,560
Speaker 1: engagement mating and all of that, all it takes is

887
00:50:35,600 --> 00:50:38,279
Speaker 1: one algorithmic tweak and then no one's You don't have

888
00:50:38,320 --> 00:50:40,960
Speaker 1: the eyeballs or the attention of the world any longer

889
00:50:41,000 --> 00:50:43,960
Speaker 1: and so yeah, it's it's a game and we're all

890
00:50:43,960 --> 00:50:44,520
Speaker 1: being played.

891
00:50:44,920 --> 00:50:51,760
Speaker 4: What can we What can the collective learn from Coffee Wife.

892
00:50:52,239 --> 00:50:54,520
Speaker 1: Something that I found really interesting about the Coffee Wife

893
00:50:54,520 --> 00:50:57,440
Speaker 1: saga was how everybody assumed she was wealthy because she

894
00:50:57,520 --> 00:51:01,600
Speaker 1: has a garden. And I found that to be really

895
00:51:01,600 --> 00:51:04,040
Speaker 1: interesting because she was like, oh, it's not like a

896
00:51:04,080 --> 00:51:06,640
Speaker 1: fancy garden. It's just a small garden in my in

897
00:51:06,680 --> 00:51:10,279
Speaker 1: my like regular home. I think that it.

898
00:51:10,239 --> 00:51:11,240
Speaker 2: Is very easy.

899
00:51:11,920 --> 00:51:14,160
Speaker 1: And I say this because I've done it to trick

900
00:51:14,239 --> 00:51:17,319
Speaker 1: yourself into thinking, like, the things that I want I

901
00:51:17,360 --> 00:51:19,799
Speaker 1: can't have. I am, I am, I could never have

902
00:51:19,840 --> 00:51:23,200
Speaker 1: a garden. And I think that that really the Coffee

903
00:51:23,200 --> 00:51:27,960
Speaker 1: wife thing really showed me that a lot of us

904
00:51:28,440 --> 00:51:31,359
Speaker 1: feel like we can't have things that we actually can have.

905
00:51:31,680 --> 00:51:33,879
Speaker 1: I don't know if that makes sense, but the fact

906
00:51:33,920 --> 00:51:35,480
Speaker 1: that so many people were like, well, you have to

907
00:51:35,480 --> 00:51:37,640
Speaker 1: be rich to have a garden, and it's like, well, actually,

908
00:51:38,360 --> 00:51:39,920
Speaker 1: I don't think that's the case, and people who are

909
00:51:39,920 --> 00:51:41,920
Speaker 1: not rich have gardens all the time, and like, why

910
00:51:41,960 --> 00:51:44,439
Speaker 1: are you assuming that the pastime of gardening is something

911
00:51:44,480 --> 00:51:46,560
Speaker 1: that only the wealthy can do? Even if you live

912
00:51:46,560 --> 00:51:48,400
Speaker 1: in a small apartment you can still have like a

913
00:51:48,440 --> 00:51:49,520
Speaker 1: window garden or something.

914
00:51:49,880 --> 00:51:50,120
Speaker 2: I think.

915
00:51:50,520 --> 00:51:52,440
Speaker 1: I think it's easy to trick ourselves into thinking the

916
00:51:52,480 --> 00:51:53,759
Speaker 1: things that we want we cannot have.

917
00:51:54,120 --> 00:51:56,320
Speaker 2: So that's one two.

918
00:51:56,480 --> 00:51:59,960
Speaker 1: I would say, Yeah, we really have to be better

919
00:52:01,000 --> 00:52:05,120
Speaker 1: at understanding where we put our pain and who we

920
00:52:05,160 --> 00:52:09,160
Speaker 1: make the proxies for our pain. I would say, if

921
00:52:09,200 --> 00:52:12,520
Speaker 1: the person you are tweeting at cannot change the circumstances

922
00:52:12,520 --> 00:52:15,120
Speaker 1: that you're upset about, maybe you're putting your rage and

923
00:52:15,120 --> 00:52:17,719
Speaker 1: your anger and your emotionality in the wrong place, and

924
00:52:17,760 --> 00:52:21,480
Speaker 1: that we should direct our rage and anger and emotionality

925
00:52:21,640 --> 00:52:22,520
Speaker 1: to the right places.

926
00:52:22,600 --> 00:52:22,759
Speaker 2: Right.

927
00:52:23,120 --> 00:52:26,680
Speaker 1: I know those places tend to be structural and institutional

928
00:52:26,960 --> 00:52:30,600
Speaker 1: and faithless, but we gotta really have a sense of

929
00:52:30,640 --> 00:52:33,840
Speaker 1: what forces are actually making us unhappy. And it's probably

930
00:52:33,880 --> 00:52:35,640
Speaker 1: not this lady drinking coffee in her garden.

931
00:52:36,760 --> 00:52:39,040
Speaker 4: Thank you so much to bridget Todd. Listen to there

932
00:52:39,080 --> 00:52:41,920
Speaker 4: are no girls on the internet every single week, I

933
00:52:42,040 --> 00:52:47,760
Speaker 4: sure do. So what became of our coffee wife legend?

934
00:52:48,360 --> 00:52:51,319
Speaker 4: Daisy didn't respond to my request for an interview, and

935
00:52:51,480 --> 00:52:54,080
Speaker 4: I respect that she just wants to be a person

936
00:52:54,280 --> 00:52:57,840
Speaker 4: who does pleasant things with people she likes. Some people

937
00:52:58,000 --> 00:53:01,400
Speaker 4: just don't want a dumb bitch podcast interfering with their life,

938
00:53:01,440 --> 00:53:04,080
Speaker 4: and I have to accept that. As far as her

939
00:53:04,160 --> 00:53:09,000
Speaker 4: online persona, Daisy is no longer Coffee Wife. She is

940
00:53:09,120 --> 00:53:12,279
Speaker 4: Daisy and appears to be spending her time generally not

941
00:53:12,520 --> 00:53:16,400
Speaker 4: on Twitter nowadays. She lives in Bali, India and is

942
00:53:16,480 --> 00:53:19,759
Speaker 4: returning to her lashes business later in the year. I

943
00:53:19,840 --> 00:53:23,320
Speaker 4: have no idea if she's a wife, if she drinks coffee,

944
00:53:23,480 --> 00:53:27,440
Speaker 4: but she's certainly Daisy, and I like Daisy, and with

945
00:53:27,600 --> 00:53:38,240
Speaker 4: that the coffee wife. Your sixteenth minute ends. Now, Okay,

946
00:53:39,239 --> 00:53:42,760
Speaker 4: I'm on the couch with my boyfriend drinking coffee close enough.

947
00:53:43,840 --> 00:53:44,719
Speaker 5: Oh I should I guess it?

948
00:53:44,760 --> 00:53:45,239
Speaker 4: Should hold?

949
00:53:45,400 --> 00:53:46,080
Speaker 6: I should hold it.

950
00:53:46,120 --> 00:53:47,240
Speaker 4: You're right, get your coffee.

951
00:53:47,280 --> 00:53:50,040
Speaker 5: Yeah, but hey, coffee in the morning, even after I've

952
00:53:50,080 --> 00:53:52,960
Speaker 5: gotten off my damn shift, coffee with my wife.

953
00:53:55,160 --> 00:53:57,600
Speaker 4: And we don't have a garden. We do have a

954
00:53:59,239 --> 00:54:01,920
Speaker 4: little deck, but I just kind of we have.

955
00:54:01,880 --> 00:54:06,800
Speaker 5: A bug in the house though, Casper Casper bugs.

956
00:54:07,040 --> 00:54:08,200
Speaker 4: We do two bugs.

957
00:54:08,239 --> 00:54:10,399
Speaker 8: I just the deck kind of stresses me out because

958
00:54:10,440 --> 00:54:12,680
Speaker 8: there's so much pollution. Who were across the street from

959
00:54:12,680 --> 00:54:15,400
Speaker 8: a We shouldn't say where, we know.

960
00:54:15,600 --> 00:54:18,319
Speaker 5: We should, but you can visualize the pollution because we

961
00:54:18,360 --> 00:54:21,160
Speaker 5: can see all of the gathering dust, so much dust,

962
00:54:21,239 --> 00:54:22,319
Speaker 5: the accumulated dusts.

963
00:54:22,440 --> 00:54:25,120
Speaker 4: So you just walked up to Casper and started kissing him.

964
00:54:25,280 --> 00:54:30,480
Speaker 9: They are, they're kissing right now. There is looking Casper's forehead.

965
00:54:30,360 --> 00:54:33,600
Speaker 4: You love saying you're so dirty, You're so dirty. They're

966
00:54:33,680 --> 00:54:34,400
Speaker 4: the same size.

967
00:54:34,440 --> 00:54:34,560
Speaker 5: Now.

968
00:54:34,600 --> 00:54:35,080
Speaker 1: It's great.

969
00:54:37,239 --> 00:54:39,319
Speaker 5: We could try this in a garden at some point though,

970
00:54:39,440 --> 00:54:39,960
Speaker 5: don't you think.

971
00:54:45,440 --> 00:54:48,200
Speaker 4: Sixteenth Minute is a production of cool Zone Media and

972
00:54:48,239 --> 00:54:51,840
Speaker 4: iHeart Radio. It is written, posted, and produced by me

973
00:54:52,120 --> 00:54:55,680
Speaker 4: Jamie Loftus. Our executive producers are Sophie Lichtman and Robert

974
00:54:55,680 --> 00:55:00,480
Speaker 4: Evans lemizing. Ian Johnson is our supervising producer and our editor.

975
00:55:00,920 --> 00:55:04,719
Speaker 4: Our theme song is by Sad thirteen. Special thanks to

976
00:55:04,800 --> 00:55:08,439
Speaker 4: Brant Crater and Sophie Lichterman for doing voiceover and pet

977
00:55:08,480 --> 00:55:11,399
Speaker 4: shout outs to our dog producer Anderson, my cats Flee

978
00:55:11,400 --> 00:55:13,960
Speaker 4: and Casper, and my pet Rock Bert, who will outlive

979
00:55:14,040 --> 00:55:15,080
Speaker 4: us all Ye