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Speaker 1: Cool zone media.

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Speaker 2: Okay, I don't know if you've heard this one, but

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Speaker 2: being a woman on the internet sucks.

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Speaker 3: It is bad.

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Speaker 2: It is so bad that maybe you just rolled your

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Speaker 2: eyes at hearing me say it, like, well, a white

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Speaker 2: millennial just said being a woman online is actually really hard,

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Speaker 2: and not to be that brave white millennial. But yes,

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Speaker 2: it really sucks being a woman on the internet, and

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Speaker 2: it sucks so much that it's bad writing for me

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Speaker 2: to even tell you that. But if you're a woman, girl,

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Speaker 2: non binary, really just not a cis man online and

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Speaker 2: other random online users know that, particularly anonymous people, you'll

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Speaker 2: get a crash course in gender discrimination the likes of

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Speaker 2: which you could not imagine. And of course this happens

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Speaker 2: across many lines, and intersecting marginalized identities tends to mean

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Speaker 2: worse abuse. That's why we have terms like misogynir to

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Speaker 2: describe the elevated prejudice that black women experience, or why

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Speaker 2: a study from the National Library of Medicine found that

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Speaker 2: gendered racism against Asian American women has gotten worse in

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Speaker 2: recent years, causing a community wide decrease in mental health.

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Speaker 2: Trans women face threats of violence and violent actions at

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Speaker 2: four times the rate of CIS women, compounded by the

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Speaker 2: world's most powerful countries passing laws that invalidate their existence

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Speaker 2: at best and enable transgenocide at worst. And that's just

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Speaker 2: studies that address people who identify as women. Non Binary

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Speaker 2: people face a whole separate type of discrimination. There's billions

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Speaker 2: of ways to be a woman online and most of

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Speaker 2: them fucking suck. And that's because being a woman anywhere

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Speaker 2: still tends to fucking suck. That's one of the first

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Speaker 2: things you learn on the internet. Don't be marginalized in

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Speaker 2: any way, or someone's going to threaten to kill you.

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Speaker 2: You could also fall in love or meet your best

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Speaker 2: friend in my case, all of the above. That's the

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Speaker 2: monkey paw of logging in. It's why when I was

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Speaker 2: twelve and posting on message boards lying out of my

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Speaker 2: app pretending to be a nineteen year old boy named

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Speaker 2: Aaron who wanted to store the band, I got legitimate

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Speaker 2: replies and asked what my favorite bands were. And when

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Speaker 2: I panicked and admitted I was a twelve year old girl,

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Speaker 2: the same people started asking me for pictures of myself

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Speaker 2: really cool stuff. And while there were many main characters

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Speaker 2: of the Internet who became notorious or were pilloried for

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Speaker 2: doing something. A father refuses to open a can of

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Speaker 2: beans for his daughter to teach her a lesson. A

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Speaker 2: husband loves his curvw wife a little too weird. And

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Speaker 2: then there are others who become the character of the

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Speaker 2: day for simply existing online. Come with me if you

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Speaker 2: will to October twenty twenty two. Shouldn't be a super

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Speaker 2: heavy lift. You know it's not not recent. The day

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Speaker 2: was October twenty first. Kim Kardashian tried to go to

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Speaker 2: a fancy restaurant and an usher concert for her forty

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Speaker 2: second birthday, but ends up at an in and Out instead.

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Speaker 2: Liz Trust becomes the shortest lived UK Prime Minister of

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Speaker 2: all time and really designs after only six weeks. Midnights

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Speaker 2: by Taylor Swift comes out, introducing the extremely unpleasant lyric Someday,

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Speaker 2: I feel like everybody is a sexy baby into the world. Swifties,

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Speaker 2: Please don't contact me. I'm having a hard time right

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Speaker 2: now and I can't deal with you. Yes, October twenty

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Speaker 2: twenty two. In two short weeks, I would give a

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Speaker 2: speech at my friend's wedding and meet the man who

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Speaker 2: would ruin my life For the next nine months next

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Speaker 2: to a porta potty. So here's some obvious advice I

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Speaker 2: can give you. Never talk to a man you meet

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Speaker 2: next to a porta potty. The point is being a

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Speaker 2: woman online or in the world, or me specifically, is

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Speaker 2: a pain in the ass, and our main character is terrific.

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Speaker 2: Proof of that with a healthy dose of class dynamic

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Speaker 2: discussion to boot the wife who drank coffee in the garden,

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Speaker 2: your sixteenth minute begins. Now that's.

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Speaker 4: Stay.

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Speaker 2: On the morning of October twenty first, twenty twenty two,

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Speaker 2: a twenty four year old woman named Daisy tweeted the

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Speaker 2: following from her Twitter account at litl Plant.

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Speaker 1: Mommy, my husband and I wake up every morning and

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Speaker 1: bring our coffee out to her garden and sit in

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Speaker 1: for hours every morning. It never gets old and we

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Speaker 1: never run out of things to talk to.

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Speaker 2: Love him so much, I know, really fucked up stuff.

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Speaker 2: The story here is young woman enjoys coffee and talking

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Speaker 2: with her husband for long periods of time. The reaction

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Speaker 2: to this story, well.

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Speaker 5: I wake up every day with chronic pain carcel tunnel

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Speaker 5: syndrome and wash my OCD medication down with an iced

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Speaker 5: oat milk lattee.

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

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Speaker 2: Put?

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

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Speaker 6: and stuff?

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Speaker 3: Lol?

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Speaker 5: This is cute and no all that did you think

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Speaker 5: of all the people who wake up to where it

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Speaker 5: grueling hours, wake up on this streets alone or with

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Speaker 5: chronic pain? Before posting this, you should be mindful next

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Speaker 5: time before bragging about your picture perfect life. You might

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Speaker 5: 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. That is, unless you're flogging something.

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Speaker 5: Very nice story, But haven't you been married for less

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Speaker 5: than four months? This phase will end, It always does.

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Speaker 5: Please don't be disheartened when it does. Remember love is

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Speaker 5: 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. They

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

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Speaker 3: They are capitalism.

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Speaker 2: They don't even control the railways or the flow of commerce.

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Speaker 2: I know it's not the same thing, but it feels

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Speaker 2: like the same thing. I mean, Twitter is undefeated for

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Speaker 2: finding me only people on earth who can be crueler

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Speaker 2: to you than your own negative self talk, and that's

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Speaker 2: just a fact. But to be honest, I was in

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Speaker 2: a bad enough place when I saw this story that

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Speaker 2: while I recognized that the backlash to this poor woman

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Speaker 2: was ridiculous, I kind of resented her to every day.

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Speaker 2: I'm doing well financially, but I don't have talking to

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Speaker 2: my partner for hours in the garden every day money.

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Speaker 2: I don't even think I have garden money. And at

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Speaker 2: the time, I hadn't met anyone to either drink coffee

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Speaker 2: with or ruin my life with. But to my credit,

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Speaker 2: I had the wisdom to not participate in this discourse.

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Speaker 2: I did what I think is the much safer move,

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Speaker 2: thought about it privately, and kept my fucking mouth shut.

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Speaker 2: At the time I'm writing this, this tweet from at

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Speaker 2: Little Plant Mommy has three hundred and fourteen thousand likes.

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Speaker 2: This is about as close as it gets to a

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Speaker 2: full on public siahhing for saying something that isn't only

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Speaker 2: innocuous on its face, but also doesn't appear to be

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Speaker 2: courting attention outside of Daisy's Twitter circle at this time,

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Speaker 2: I think she technically qualifies as a micro influencer, so

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Speaker 2: less than twenty thousand followers, not just a rando talking

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Speaker 2: to people she only knows in real life, but by

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Speaker 2: no means someone who is courting a massive audience. You

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Speaker 2: probably follow one hundred people like this. I'm basically this,

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Speaker 2: And at the time this tweet was posted, Daisy had

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Speaker 2: a discernible aesthetic and things that she talked to her

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Speaker 2: audience about frequently, so for her, this tweet wouldn't have

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Speaker 2: been outside of the realm of a very normal post

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Speaker 2: that she would make about a year before this, the

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Speaker 2: only other time the Wayback Machine Internet.

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Speaker 3: Archives saved her page.

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Speaker 2: Daisy's bio read as.

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Speaker 1: Follows naturopathic medicine student, white woman's student emoji, licensed holistic

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Speaker 1: beauty specialist, branch emoji, sustainable gardener, white woman gardener emoji.

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Speaker 2: A few months before the tweet that shook the Earth,

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Speaker 2: she got married to a man named Matt who it

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Speaker 2: seems like she loved a whole lot. That's it, and

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Speaker 2: her tweets were maybe what you'd expect based on that

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Speaker 2: pretty niche with a lot of slightly woo woo wellness

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Speaker 2: talk that isn't for everyone, but wasn't trying to be.

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Speaker 2: As I read through some of her old stuff, I

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Speaker 2: didn't agree with some of it. I mean, I don't

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Speaker 2: think Dary is as bad as all that, but honestly,

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Speaker 2: I probably never would have found her account if it

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Speaker 2: weren't for this story. People with as many seven to

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Speaker 2: eleven loyalty points as I do are simply not buying

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Speaker 2: what our girl Daisy is selling. And by the way,

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Speaker 2: the reaction that some of these response tweets imply suggests

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Speaker 2: that Daisy owned a business that personified the grueling puppy

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Speaker 2: mill that is capitalism with the same energy as if

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Speaker 2: she were Jeff Bezos himself. Again, not true. Daisy ran

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Speaker 2: a small time esthetician business called The Holistic Esthetician, and

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Speaker 2: there's nothing wrong with that outside of being a little

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Speaker 2: hard for me to say. It doesn't even seem like

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Speaker 2: she has employees, and that might also explain her flexible hours.

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Speaker 2: And I can't emphasize enough that for this fairly small

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Speaker 2: account less than twenty thousand followers, this was not an

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Speaker 2: unusual post. The tweets posted around the same time were

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Speaker 2: pretty similar.

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Speaker 1: The perfect balance of love and light but also real

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Speaker 1: raw and imperfect is what I'm always striving for. Balance. Baby,

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Speaker 1: that some highlights and a couple haircuts yesterday after months

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Speaker 1: of not doing hair, and they both turned out so

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Speaker 1: pretty makes me missdoing hair?

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Speaker 2: So why did this tweet about drinking coffee in the

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Speaker 2: garden blow up the Twitter algorithm? In a recent episode,

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Speaker 2: I spoke with Taylor Lorenz about the phenomenon of the dress,

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Speaker 2: and while Coffee Wife isn't a story she reported on

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Speaker 2: at the time, she has a lot of experience in

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Speaker 2: tracking stories like this, and what she found instructive about

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Speaker 2: the drinking coffee in the garden story wasn't that it

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Speaker 2: was more upsetting than your average woman doing something and

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Speaker 2: getting yelled at online story. It was that the stories

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Speaker 2: boost in the algorithm required both backlash to what Daisy

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Speaker 2: said and backlash to the backlash. Here's some of our

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Speaker 2: 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, is

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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.

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Speaker 7: Initially people and.

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Speaker 8: I think I mean districtly based on how the engagement

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

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

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Speaker 9: Well, but it was not.

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Speaker 7: It was an equal parts let's yell at her and

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Speaker 7: then people getting outraged that people were yelling at her,

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Speaker 7: And that is It's really important to have like both

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Speaker 7: of those, I think to reach the level of virality

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Speaker 7: that this did. But you know this is right, like

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Speaker 7: since Twitter has been leaning harder and harder into algorithmic

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Speaker 7: recommendations for years, but I think we've really seen it,

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Speaker 7: especially since the Elon era like really take hold. And

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Speaker 7: I think this is an example of Twitter leaning hard

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Speaker 7: into algorithmic recommendations where suddenly this person is in your

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Speaker 7: feed because everybody has an opinion on the commentary about it.

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Speaker 7: And everybody wants to again project, they want to use

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Speaker 7: this innocuous, benign, sort of generic tweet as a way

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Speaker 7: to posture about whatever 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 the story doesn't

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Speaker 8: really thrive unless.

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Speaker 2: She also has thousands of people coming to her defense,

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Speaker 2: even though she's tweeting, you know, into presumably to her

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Speaker 2: the void.

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Speaker 8: Do you remember when that sort of phenomenon.

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

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

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Speaker 7: about door dash. Some person talked about door dash and

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Speaker 7: suddenly it was like five days of discourse of people

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Speaker 7: outraged about DoorDash, and then people outraged about the outrage.

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Speaker 7: But the outrage at people that are expressing they're very

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Speaker 7: you know, first of all, they shouldn't be expressing it

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Speaker 7: at that woman. But I can understand things are triggering

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Speaker 7: on the internet. Whatever they get triggered, but then it's

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Speaker 7: like the other people getting very triggered that anybody is triggered,

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

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Speaker 7: I think I'll so, just we're dealing with a lot

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

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

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Speaker 7: that can affect change and have institutional power don't give

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Speaker 7: a shit what average people have to say if they

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Speaker 7: don't have money or access themselves to power. So these

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Speaker 7: main characters kind of become the only outlet for voicing

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Speaker 7: this anger, and people are used as props to make

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

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Speaker 7: 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 coore misogyny. And then there's of course a

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Speaker 7: separate type of really vicious hatred towards women of color

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Speaker 7: or also just ripped apart constantly. The thing is, they

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Speaker 7: don't really have the level of privilege, and so they

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Speaker 7: often some 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 that people are

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

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Speaker 7: 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 misogynis on

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Speaker 7: the internet. Love to come for Yeah, thanks.

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Speaker 2: Again to Taylor. Her book Extremely Online is available now.

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Speaker 2: So talking with Taylor reset how I was thinking about

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Speaker 2: this story a little. So to say that the legacy

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Speaker 2: of Coffee Wife is that people hate women online is

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Speaker 2: technically true, but a little undercooked. After talking to Taylor,

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Speaker 2: I'm convinced that this story is also a pretty damning

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Speaker 2: example of modern online algorithms gaming us to engage with

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Speaker 2: each other. Because, as I was going back through the

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Speaker 2: quote tweets reacting to Daisy's bold statement, the mean tweets

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Speaker 2: versus the defenses of Daisy are uneven. There's more nice

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Speaker 2: comments coming to her defense for every tweet that says

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Speaker 2: they are capitalism.

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Speaker 3: 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 2: I can't afford coffee. The only thing I have to

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Speaker 2: drink in the garden is bird bathwater. Because I'm a robin,

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Speaker 2: I'm an actual bird. This tweet is not relatable to

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Speaker 2: my experience as a literal bird. I can't get a

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Speaker 2: house because I'm a bird and can't apply for a mortgage.

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Speaker 6: Privileged bitch eat the rich has gone from no one

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Speaker 6: should be a billionaire to no one living above the

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Speaker 6: poverty level treating themselves and their husband to morning coffee

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Speaker 6: and their gardens should be happy.

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

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

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

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

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Speaker 2: And when it comes to the algorithm, once you've got

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Speaker 2: a class war about the class war, you are cooking.

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Speaker 2: In one of the last interviews Daisy gave on the

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Speaker 2: subject in December twenty twenty two with YouTuber and Jellylouz,

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Speaker 2: she described what it was like experiencing these waves of

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Speaker 2: discourse in what felt like a void.

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Speaker 4: It just kind of like blew up within like ten

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Speaker 4: hours of it posting. I posted it, I noticed that

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Speaker 4: like a lot of people were like commenting and liking it,

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Speaker 4: and it was kind of going a little viral, and

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Speaker 4: like by the next day that I had posted it,

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Speaker 4: it was just like totally blown up with lots of

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Speaker 4: like lots of negativity and lots of like hate comments

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Speaker 4: and people saying all kinds of like crazy stuff about

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Speaker 4: me and my husband, and that kind of continued. The

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Speaker 4: negativity kind of continued for a little bit, but it

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Speaker 4: got to the point by like day like two or

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Speaker 4: three where like everybody was just coming in on the

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Speaker 4: post and being like this is actually so cute and

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Speaker 4: so nice, and like forget about all the haters and

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Speaker 4: like all of that stuff. And I feel like, I

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Speaker 4: mean when I try to go into the tweet and

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Speaker 4: like look for the negativity, I literally can't find negative

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Speaker 4: comments anymore because there's been so many thousands of people

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Speaker 4: that have just like drowned all of the like meanness

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Speaker 4: in positivity and kindness and love. And so then I

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Speaker 4: kind of think that it like went in this wave

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Speaker 4: of like negativity, and then there was like another wave

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Speaker 4: where it was like where it got more popular, but

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Speaker 4: then it was like turned into something really sweet and positive.

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Speaker 2: She goes on to describe the few days of constant

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Speaker 2: attention and requests for comment by embracing the Coffee Lady persona,

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Speaker 2: even briefly adding it to her Twitter bio. And not

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Speaker 2: everyone would be able to do this, but she takes

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Speaker 2: it in stride, leaning into jokes that suggest that this

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Speaker 2: was all some big, evil plan. She tweets things like this,

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Speaker 2: this was all actually a big plot to draw everybody

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Speaker 2: in and then teach them about how to grow their

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Speaker 2: own food and heal the earth plant emoji and general

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Speaker 2: reflections on the weird, still developing media cycle of those

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Speaker 2: last few days in October, she directly confronts the criticism

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Speaker 2: in a gentle series of tweets.

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Speaker 1: It's really sad to look at the thousands of hateful

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Speaker 1: comments on this post, most saying spending time with your

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Speaker 1: spouse is only for the rich, jobless trust fund kids,

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Speaker 1: saying our marriage won't last. It really shows why a

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Speaker 1: lot of marriages probably don't last. It's one thing to

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Speaker 1: get to spend hours a day with your partner, We

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Speaker 1: are very blessed, But most of the replies are implying

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Speaker 1: that couples shouldn't have to spend time together and if

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Speaker 1: they do you must be rich, y'all are truly silly,

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Speaker 1: but thank you to all the sweet comments. I love

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Speaker 1: you so much, double heart emoji.

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Speaker 2: And to directly address her haters who claimed that she

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Speaker 2: was capitalism, Daisy tweeted this.

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Speaker 1: To answer your questions, we are not rich by any means.

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Speaker 1: We've worked extremely hard to get to where we're at.

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Speaker 1: We live very minimally and consciously and work jobs that

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Speaker 1: match our lifestyle and allow us to live the life

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Speaker 1: that we do. Thank you for all the love that

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Speaker 1: uplifting comments. You know who you are red heart emoji.

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Speaker 2: Daisy threads the needle pretty beautifully here.

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Speaker 7: Then.

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Speaker 2: I think this is a good example of how women

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Speaker 2: have to conduct themselves very carefully online to not get

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Speaker 2: anger from people. She's not ignoring it, but if it

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Speaker 2: does upset her in any way, which it could be

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Speaker 2: justified to do, she doesn't indicate that publicly. She and

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Speaker 2: her husband post a number of other pictures in their garden,

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Speaker 2: which it turns out is where they live in a

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Speaker 2: community in northern California, where he teaches yoga and she

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Speaker 2: runs her small esthetician business. They tweeted pictures of them

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Speaker 2: eating breakfast, drinking the famous coffee, and while they never

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Speaker 2: dropped their tax returns or the degree of privilege that

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Speaker 2: they grew up with, the question is, why should they

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Speaker 2: have to? Because the algorithm said so, There's no way

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Speaker 2: around it. This story was tailor made for the Internet

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Speaker 2: rage machine. Box writer Rebecca Jennings referenced as much in

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Speaker 2: a December twenty twenty two essay called every chronically online

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Speaker 2: conversation is the same, saying if you felt a creeping

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Speaker 2: sense of dread while reading about Daisy and her husband

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Speaker 2: enjoying coffee in their garden, it's possible you spend too

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Speaker 2: much time online. That's because despite it seeming innocuous, Daisy's

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Speaker 2: post has all the markers of Twitter rage bait, and

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Speaker 2: by rage bait, I mean a person sharing an experience

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Speaker 2: that may not be entirely universal. I mostly agree with

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Speaker 2: this and do feel that the anger towards Daisy is

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Speaker 2: wildly misplaced. This is the kind of anger we reserve

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Speaker 2: for Kardashians throwing parties during a pandemic, and this doesn't

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Speaker 2: invalidate any of the anger or frustration that online users

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Speaker 2: that were truly sorry triggered by Daisy's inoffensive post. Fault

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Speaker 2: I mean hell, Daisy herself articulated this feeling better than

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Speaker 2: anyone else here. She is on that same Angelilou's YouTube podcast.

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Speaker 4: You know, as far as what I could say to

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Speaker 4: the people that were doing all of that is, I

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Speaker 4: just think when you're exuding that much hate to other people,

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Speaker 4: that comes from a place in your heart that's hurt,

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Speaker 4: because I truly believe that you know everything that like,

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Speaker 4: we're all just mirrors of each other, and something about

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Speaker 4: me made them feel something about themselves that was probably

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Speaker 4: trauma from who knows when in their life, and that

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Speaker 4: caused something and caused them to feel that way. So

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Speaker 4: I think that that just comes. That kind of behavior

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Speaker 4: just comes from someone being hurt. And I understand that,

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Speaker 4: and I have compascity for those people because truly, maybe

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Speaker 4: they know better, but they probably don't know any better.

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Speaker 4: They're just dealing with their hurt and they're dealing with

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Speaker 4: it like that instead of in other healthy ways.

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Speaker 3: You know.

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Speaker 2: So thankfully Coffee Wife had a mellow enough lifestyle to

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Speaker 2: forgive and was offline enough to understand the anger without

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Speaker 2: becoming enraged. Back when it comes to women behaving in

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Speaker 2: a very particular way to not get a particular reaction.

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Speaker 2: Daisy did everything right. All she did wrong was exist

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Speaker 2: in a way that the algorithm was liable to boost.

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Speaker 2: When I started this show, the person who was most insistent,

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Speaker 2: along with hundreds of others that I talk about coffee wife,

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Speaker 2: was my best friend Julia, and I wanted to know why,

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Speaker 2: because no matter where you fell at the time, what

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Speaker 2: happened over the coffee in the garden tweet was a

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Speaker 2: pretty classic public shaming. And Julia is a great comic

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Speaker 2: and writer who wrote a controversial essay for Gawker in

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Speaker 2: twenty twenty two called in Defense of Shame. She's literally

438
00:25:02,640 --> 00:25:05,600
Speaker 2: an authority on shame, and not just because she grew

439
00:25:05,680 --> 00:25:08,359
Speaker 2: up Catholic in New England. But that certainly didn't hurt,

440
00:25:08,680 --> 00:25:12,959
Speaker 2: and Julia feels strongly that Daisy was not deserving of

441
00:25:13,000 --> 00:25:16,639
Speaker 2: the backlash she got. So when is shame a necessary

442
00:25:16,680 --> 00:25:19,639
Speaker 2: tool and when is it? Whatever the fuck this is,

443
00:25:19,880 --> 00:25:22,080
Speaker 2: I wanted to ask her about it first.

444
00:25:22,440 --> 00:25:26,840
Speaker 9: I am Julia Claire. I'm a comedian and writer at

445
00:25:26,960 --> 00:25:27,720
Speaker 9: Crooked Media.

446
00:25:28,520 --> 00:25:32,199
Speaker 2: You are the person that I associate most with like

447
00:25:32,600 --> 00:25:34,280
Speaker 2: intensely feeling about this story.

448
00:25:35,080 --> 00:25:37,560
Speaker 9: I am the person you most associate with the concept

449
00:25:37,600 --> 00:25:37,960
Speaker 9: of shame.

450
00:25:39,240 --> 00:25:43,479
Speaker 10: Yes, yes, and so it really you've saved me an

451
00:25:43,480 --> 00:25:49,280
Speaker 10: interview here by also because yeah, like you felt really

452
00:25:49,920 --> 00:25:54,720
Speaker 10: strongly that this woman had been shamed improperly, but you

453
00:25:54,760 --> 00:25:57,800
Speaker 10: do feel tell me your feelings about a proper shaming.

454
00:25:58,200 --> 00:26:02,000
Speaker 9: A few years ago, I wrote piece for gaker Rip

455
00:26:02,840 --> 00:26:07,560
Speaker 9: called in Defense of Shame. Was kind of immediately criticized

456
00:26:07,600 --> 00:26:10,600
Speaker 9: by people who didn't read the piece as a defense

457
00:26:10,960 --> 00:26:15,840
Speaker 9: being a defensive shaming. People were basically saying that I

458
00:26:16,080 --> 00:26:20,640
Speaker 9: was co signing dog pile culture, co signing shaming, which

459
00:26:20,680 --> 00:26:23,720
Speaker 9: is not at all what I was talking about in

460
00:26:23,760 --> 00:26:29,520
Speaker 9: the piece. I think of shame as any lapsed Catholic would.

461
00:26:29,800 --> 00:26:30,000
Speaker 2: Uh.

462
00:26:30,720 --> 00:26:37,359
Speaker 9: It's a very kind of like internal experience, more of

463
00:26:37,400 --> 00:26:43,080
Speaker 9: a reflective experience, not an external experience. Shame is for

464
00:26:43,320 --> 00:26:46,840
Speaker 9: Shame is for me. It's not for you, you know, it's

465
00:26:46,920 --> 00:26:52,199
Speaker 9: like so to me. I mean basically, like my my

466
00:26:52,240 --> 00:26:54,560
Speaker 9: defense of shame was that more people need to be

467
00:26:54,680 --> 00:26:57,720
Speaker 9: kind of in touch with their own shame. And I

468
00:26:58,200 --> 00:27:01,760
Speaker 9: honestly think that like a lot of the I think

469
00:27:01,760 --> 00:27:03,439
Speaker 9: the fact that a lot of people aren't is the

470
00:27:03,480 --> 00:27:09,240
Speaker 9: reason why they end up projecting on other people. But yeah,

471
00:27:09,280 --> 00:27:13,280
Speaker 9: this was one of those things like that was a

472
00:27:13,320 --> 00:27:18,119
Speaker 9: clear case of shaming in a way that was completely

473
00:27:18,200 --> 00:27:24,119
Speaker 9: needless and silly. Honestly, you're yelling at this twenty something

474
00:27:24,320 --> 00:27:29,600
Speaker 9: woman because she's having a lovely morning, right, kill yourself.

475
00:27:32,080 --> 00:27:38,080
Speaker 2: Is there a productive way to shame someone on the internet.

476
00:27:39,680 --> 00:27:43,480
Speaker 9: That's a really good question. I think you have to.

477
00:27:43,720 --> 00:27:46,520
Speaker 9: I think if there is, you really have to be

478
00:27:46,600 --> 00:27:49,600
Speaker 9: punching up. Like the whole thing with Coffee wife is

479
00:27:49,600 --> 00:27:51,879
Speaker 9: that she was just some kind of like random lady.

480
00:27:52,280 --> 00:27:52,480
Speaker 2: Right.

481
00:27:52,560 --> 00:27:55,520
Speaker 9: It's very different if we're all piling on to like

482
00:27:55,960 --> 00:27:58,120
Speaker 9: I mean, there are some people who are really impervious

483
00:27:58,160 --> 00:28:02,280
Speaker 9: to it. So it like, you know, Elon Musk seems

484
00:28:02,320 --> 00:28:07,200
Speaker 9: to just revel in the fact that everyone hates him.

485
00:28:09,040 --> 00:28:12,119
Speaker 9: But as far as a productive way to shame, to

486
00:28:12,240 --> 00:28:15,359
Speaker 9: shame the average per I mean no, I don't think so,

487
00:28:15,520 --> 00:28:18,600
Speaker 9: and I and I really again, I don't advocate for

488
00:28:18,840 --> 00:28:22,200
Speaker 9: shame as an external force. I think all of our

489
00:28:22,240 --> 00:28:26,280
Speaker 9: shame should be internal, and it should be between us

490
00:28:26,400 --> 00:28:30,960
Speaker 9: and the Lord. Your parents are going to be so pleased,

491
00:28:31,040 --> 00:28:36,480
Speaker 9: I know, Father Leroy at Saint Edward's Parish, your impact

492
00:28:36,480 --> 00:28:38,760
Speaker 9: has felt on this podcast absolutely.

493
00:28:41,080 --> 00:28:43,000
Speaker 2: Thank you so much to my best friend Julia Claire.

494
00:28:43,240 --> 00:28:46,760
Speaker 2: But you can catch every day over at Crooked Media

495
00:28:46,800 --> 00:28:50,200
Speaker 2: and we'll be right back with more of Coffee Wife's

496
00:28:50,480 --> 00:29:07,360
Speaker 2: sixteenth minute. Welcome back to sixteenth minute today. I've had

497
00:29:07,400 --> 00:29:10,120
Speaker 2: six cups of coffee and still no husband in sight.

498
00:29:10,640 --> 00:29:14,360
Speaker 2: We're talking coffee wife. So not to twenty sixteen ghostbusters

499
00:29:14,440 --> 00:29:17,440
Speaker 2: this situation. But take a second to imagine how this

500
00:29:17,560 --> 00:29:20,800
Speaker 2: story would be different if it were a husband tweeting

501
00:29:20,840 --> 00:29:24,720
Speaker 2: about enjoying time with his wife in said garden. I

502
00:29:24,800 --> 00:29:27,080
Speaker 2: really don't think the reaction would be the same. In

503
00:29:27,120 --> 00:29:31,120
Speaker 2: the context of hetero couples. Husbands who adore their wives

504
00:29:31,320 --> 00:29:34,160
Speaker 2: tend to be lifted up as wife guys in the

505
00:29:34,160 --> 00:29:37,520
Speaker 2: same way that they're more easily rewarded socially for being

506
00:29:37,560 --> 00:29:40,280
Speaker 2: an active part of their children's lives. And while there's

507
00:29:40,360 --> 00:29:44,240
Speaker 2: intersecting issues that caused people to project onto Coffee Wife,

508
00:29:44,560 --> 00:29:46,960
Speaker 2: I still think this boiled down to an Internet classic.

509
00:29:47,280 --> 00:29:50,560
Speaker 2: Women are fair game for just about anything. There's no

510
00:29:50,760 --> 00:29:54,400
Speaker 2: social incentive for Daisy to say she loves her husband,

511
00:29:54,680 --> 00:29:57,640
Speaker 2: because when a woman adores spending time with her husband,

512
00:29:58,000 --> 00:30:00,479
Speaker 2: so what it would be selfish of her and not

513
00:30:00,520 --> 00:30:03,000
Speaker 2: love spending time with him when a woman takes good

514
00:30:03,080 --> 00:30:06,920
Speaker 2: care of and loves her children, So what, That's the

515
00:30:07,000 --> 00:30:10,520
Speaker 2: natural expectation, and coming up short in either department is

516
00:30:10,560 --> 00:30:14,680
Speaker 2: still met with easier, more reflexive criticism, even with gains

517
00:30:14,720 --> 00:30:16,560
Speaker 2: made in general gender perception.

518
00:30:16,920 --> 00:30:18,520
Speaker 3: But while I do firmly.

519
00:30:18,160 --> 00:30:21,880
Speaker 2: Believe that Daisy was dragged online for simply being happy,

520
00:30:22,480 --> 00:30:24,920
Speaker 2: I want to state the obvious and say, of course

521
00:30:25,160 --> 00:30:28,400
Speaker 2: women can fucking suck online. There's plenty of precedent for that,

522
00:30:28,560 --> 00:30:32,320
Speaker 2: because women are people, and there are clear patterns en

523
00:30:32,400 --> 00:30:36,440
Speaker 2: mass and as individuals for assists white women specifically like

524
00:30:36,560 --> 00:30:40,440
Speaker 2: Daisy and myself, to behave in an insensitive at best,

525
00:30:40,840 --> 00:30:44,760
Speaker 2: bigoted and benefiting from the whiteness that patriarchy and capitalism rewards,

526
00:30:44,800 --> 00:30:46,760
Speaker 2: and being generally a condescending piece of shit to people

527
00:30:46,760 --> 00:30:50,120
Speaker 2: who are more marginalized than themselves. That's a lot of

528
00:30:50,160 --> 00:30:53,600
Speaker 2: words to say a no longer trendy term that is

529
00:30:53,640 --> 00:30:57,840
Speaker 2: still somewhat useful, and it is girl boss. There's a

530
00:30:57,840 --> 00:31:00,800
Speaker 2: bunch of conflicting definitions of this term. Some are as

531
00:31:00,800 --> 00:31:04,360
Speaker 2: simple as quote a woman, especially a young woman who

532
00:31:04,480 --> 00:31:08,120
Speaker 2: is ambitious and successful in her career unquote, and others

533
00:31:08,240 --> 00:31:10,480
Speaker 2: as I think of the girl boss are connected more

534
00:31:10,480 --> 00:31:14,320
Speaker 2: closely to women using the language of feminism to accrue

535
00:31:14,360 --> 00:31:18,640
Speaker 2: power while actively upholding the status quo. Probably the most

536
00:31:18,680 --> 00:31:21,560
Speaker 2: famous example of this is Sheryl Sandberg, who wrote the

537
00:31:21,560 --> 00:31:24,680
Speaker 2: best seller Lean In in twenty thirteen to encourage women

538
00:31:24,720 --> 00:31:28,320
Speaker 2: to advocate for themselves in the workplace. She is the

539
00:31:28,480 --> 00:31:32,200
Speaker 2: ultimate girl boss to me for a few reasons. First

540
00:31:32,200 --> 00:31:35,360
Speaker 2: of all, she is a huge beneficiary of capitalism that

541
00:31:35,480 --> 00:31:39,280
Speaker 2: is actively harmful. She was the COO of Facebook during

542
00:31:39,400 --> 00:31:42,800
Speaker 2: years and years of infinite growth. And second of all,

543
00:31:43,040 --> 00:31:46,120
Speaker 2: she's using her position as a powerful woman to sell

544
00:31:46,200 --> 00:31:49,120
Speaker 2: you something and not something. Is that the only thing

545
00:31:49,160 --> 00:31:51,640
Speaker 2: holding you back as a woman in the workplace is

546
00:31:51,680 --> 00:31:54,600
Speaker 2: not the system you find yourself in, but something you

547
00:31:54,960 --> 00:31:58,000
Speaker 2: are neglecting to do it self. Helps snake oil that

548
00:31:58,160 --> 00:31:59,840
Speaker 2: bullies the women who are reading it.

549
00:32:00,080 --> 00:32:00,760
Speaker 3: Here's a quote.

550
00:32:01,800 --> 00:32:04,440
Speaker 2: I'm sorry if this sounds harsh or surprises anyone, but

551
00:32:04,560 --> 00:32:06,600
Speaker 2: this is where we are. If you want the outcome

552
00:32:06,640 --> 00:32:10,800
Speaker 2: to be different, you will have to do something about it. Oh,

553
00:32:11,120 --> 00:32:14,560
Speaker 2: it's your fault. She also says this, we need to

554
00:32:14,600 --> 00:32:18,280
Speaker 2: stop telling women get a mentor and you will excel. Instead,

555
00:32:18,320 --> 00:32:20,840
Speaker 2: we need to tell them excel and you will get

556
00:32:20,880 --> 00:32:27,120
Speaker 2: a mentor Oh it's my fault, twenty dollars well spent,

557
00:32:27,240 --> 00:32:30,280
Speaker 2: thanks Cheryl. That's the kind of girl boss shit we're

558
00:32:30,320 --> 00:32:34,720
Speaker 2: talking about. So a very instructive term that is often

559
00:32:34,760 --> 00:32:40,600
Speaker 2: misused after being sucked into this linguistic, misogynist vortex. The

560
00:32:40,640 --> 00:32:43,719
Speaker 2: difficulty with the girl boss tag gets to why I

561
00:32:43,760 --> 00:32:46,880
Speaker 2: think Coffee Wife was done so dirty. There are people

562
00:32:46,920 --> 00:32:50,120
Speaker 2: who aren't big fans of women who glommed onto this

563
00:32:50,240 --> 00:32:54,560
Speaker 2: word to use it interchangeably with all women or women

564
00:32:54,600 --> 00:32:57,480
Speaker 2: who had any power over them at work. If your

565
00:32:57,520 --> 00:33:00,520
Speaker 2: manager is a woman, that doesn't mean she is cynically

566
00:33:00,600 --> 00:33:03,720
Speaker 2: using tools of the patriarchy to oppress you while assuring

567
00:33:03,760 --> 00:33:07,720
Speaker 2: other women they're doing something wrong in order to personally profit.

568
00:33:08,080 --> 00:33:11,600
Speaker 2: It's a very specific set of behaviors, and being a

569
00:33:11,600 --> 00:33:15,000
Speaker 2: girl boss doesn't mean the women in question haven't experienced

570
00:33:15,080 --> 00:33:19,400
Speaker 2: gender discrimination themselves. In fact, I'd wager that all of

571
00:33:19,440 --> 00:33:23,720
Speaker 2: them have. This simply does not describe a woo woo

572
00:33:23,760 --> 00:33:26,560
Speaker 2: twenty four year old drinking coffee in the garden. The

573
00:33:26,600 --> 00:33:30,600
Speaker 2: anger is valid, but it is misplaced. Daisy wasn't trying

574
00:33:30,640 --> 00:33:33,360
Speaker 2: to make money by saying this. She wasn't aiming to

575
00:33:33,520 --> 00:33:37,080
Speaker 2: change minds or hurt anyone, or, according to her, even

576
00:33:37,120 --> 00:33:41,560
Speaker 2: reach outside of her normal audience. She was just sharing

577
00:33:41,600 --> 00:33:45,160
Speaker 2: something you know, like we're told is the whole point

578
00:33:45,240 --> 00:33:48,320
Speaker 2: of social media, And given the state of Twitter in

579
00:33:48,400 --> 00:33:52,440
Speaker 2: the fall of twenty twenty two and on this specific week,

580
00:33:52,680 --> 00:33:56,480
Speaker 2: the algorithm pushing this high engagement story makes a lot

581
00:33:56,520 --> 00:33:59,720
Speaker 2: of sense. There were a number of algorithmic shifts on

582
00:33:59,720 --> 00:34:02,800
Speaker 2: Twitter and in social media writ large in this year.

583
00:34:03,000 --> 00:34:05,640
Speaker 2: If you're a Twitter user yourself or I'm not going

584
00:34:05,720 --> 00:34:08,560
Speaker 2: to say X, please don't contact me about this. If

585
00:34:08,560 --> 00:34:12,319
Speaker 2: you're a Twitter user yourself or a proud Twitter retiree,

586
00:34:12,800 --> 00:34:17,520
Speaker 2: you might remember when their timeline became completely algorithmically driven

587
00:34:17,880 --> 00:34:20,080
Speaker 2: instead of what it had been for years and years,

588
00:34:20,400 --> 00:34:22,839
Speaker 2: which was a real time feed of people you had

589
00:34:22,920 --> 00:34:26,239
Speaker 2: chosen to follow. Now, people you didn't follow would be

590
00:34:26,320 --> 00:34:28,719
Speaker 2: sorted to the top of your feed if the algorithm

591
00:34:28,719 --> 00:34:31,240
Speaker 2: thought you were likely to interact with the post based

592
00:34:31,280 --> 00:34:33,880
Speaker 2: on what you'd interacted with in the past, and the

593
00:34:33,880 --> 00:34:37,719
Speaker 2: people you actually chose to follow might see their content

594
00:34:37,800 --> 00:34:42,200
Speaker 2: get pushed further and further down. Users got really pissed

595
00:34:42,239 --> 00:34:45,280
Speaker 2: off about this, and Twitter tried to mitigate the issue

596
00:34:45,320 --> 00:34:48,520
Speaker 2: by splitting everything into two feeds, So if you opened

597
00:34:48,560 --> 00:34:52,040
Speaker 2: the website on your laptop, it would default the new

598
00:34:52,320 --> 00:34:55,719
Speaker 2: shitty algorithm feed and you could shift over to the

599
00:34:55,760 --> 00:34:58,640
Speaker 2: timeline you'd had for fifteen years. But it would take

600
00:34:58,680 --> 00:35:01,839
Speaker 2: some effort, and it's ghost like daisies that would get

601
00:35:01,880 --> 00:35:05,960
Speaker 2: sorted into this new algorithmically driven feed, the one you

602
00:35:06,000 --> 00:35:08,719
Speaker 2: didn't ask for and the one that no one is

603
00:35:08,800 --> 00:35:13,000
Speaker 2: prepared to be sorted into. And within a week of

604
00:35:13,080 --> 00:35:17,319
Speaker 2: the coffee Wi flare up, a looming Twitter acquisition was

605
00:35:17,400 --> 00:35:23,320
Speaker 2: finally completed. After months of legal wrangling and negotiation, Elon

606
00:35:23,440 --> 00:35:27,520
Speaker 2: Musk has finally bought social media company Twitter. Earlier in

607
00:35:27,560 --> 00:35:30,399
Speaker 2: twenty twenty two, Elon Musk, who I think we can

608
00:35:30,480 --> 00:35:34,200
Speaker 2: all agree only had the best intentions and deserves the

609
00:35:34,239 --> 00:35:36,920
Speaker 2: benefit of the doubt, offered to buy Twitter on a

610
00:35:36,920 --> 00:35:39,840
Speaker 2: whim for fifty four dollars and twenty cents a share,

611
00:35:40,320 --> 00:35:43,399
Speaker 2: just months after he'd become the company's largest shareholder at

612
00:35:43,440 --> 00:35:46,960
Speaker 2: nearly ten percent. This put the prospective deal at forty

613
00:35:47,040 --> 00:35:51,600
Speaker 2: four billion dollars, and Twitter accepted the offer very quickly.

614
00:35:51,960 --> 00:35:54,319
Speaker 2: They genuinely didn't seem to think he'd go through with

615
00:35:54,400 --> 00:35:57,520
Speaker 2: it and accepted to all but resist a hostile takeover

616
00:35:57,600 --> 00:36:01,080
Speaker 2: from Musk, But Musk, determined to pivot the platform to

617
00:36:01,120 --> 00:36:05,200
Speaker 2: white supremacy, doubled down, declaring that his ownership would mean

618
00:36:05,320 --> 00:36:09,719
Speaker 2: less bots and more free speech. He certainly made good

619
00:36:09,760 --> 00:36:13,000
Speaker 2: on the former in the fascist content is king sense,

620
00:36:13,520 --> 00:36:16,200
Speaker 2: but the crackdown on bots is pretty hilarious for a

621
00:36:16,239 --> 00:36:19,920
Speaker 2: site that I can't even pay to stop auto posting

622
00:36:20,239 --> 00:36:23,319
Speaker 2: my pussy and bio underneath pictures of me and my

623
00:36:23,440 --> 00:36:27,239
Speaker 2: infant nephew. So yeah, this change of ownership was famously

624
00:36:27,360 --> 00:36:30,360
Speaker 2: a disaster. Elon Musk tried to back out of the

625
00:36:30,520 --> 00:36:34,239
Speaker 2: objectively bad deal that was his idea in July, but

626
00:36:34,400 --> 00:36:36,920
Speaker 2: wasn't able to and was all but forced to go

627
00:36:36,960 --> 00:36:39,840
Speaker 2: through with the deal less than a week after. Daisy

628
00:36:40,080 --> 00:36:43,759
Speaker 2: was declared the Coffee Wife, and what happened after that

629
00:36:44,000 --> 00:36:46,960
Speaker 2: was well, it's why Twitter has been in sharp decline

630
00:36:46,960 --> 00:36:50,560
Speaker 2: ever since. Just a small sampler platter of incidents since

631
00:36:50,640 --> 00:36:58,160
Speaker 2: this time, welcoming Donald Trump, Kanye and Alex Jones back

632
00:36:58,200 --> 00:37:02,480
Speaker 2: to Twitter and generally promoting, challenging Mark Zuckerberg to a

633
00:37:02,520 --> 00:37:06,160
Speaker 2: cage match, and tanking the company's net worth by over

634
00:37:06,360 --> 00:37:12,160
Speaker 2: fifty percent. There's a very depressing lens that we can

635
00:37:12,200 --> 00:37:16,360
Speaker 2: see the coffee wife incident through as this dying gasp

636
00:37:16,480 --> 00:37:20,319
Speaker 2: of old school misogyny on Twitter moments before it was

637
00:37:20,360 --> 00:37:36,759
Speaker 2: about to get much, much, much worse, and how bad

638
00:37:36,800 --> 00:37:40,200
Speaker 2: hasn't gotten on the internet since twenty twenty two. I

639
00:37:40,280 --> 00:37:43,360
Speaker 2: went to an expert, my pal Bridget Todd, host of

640
00:37:43,400 --> 00:37:47,080
Speaker 2: the Incredible podcast there are No Girls on the Internet.

641
00:37:47,520 --> 00:37:50,440
Speaker 2: Here's our chat. My name is Bridget Todd.

642
00:37:50,560 --> 00:37:53,120
Speaker 11: I am the host and creator of Iheartradios Tech and

643
00:37:53,120 --> 00:37:56,120
Speaker 11: culture podcast. There are no girls on the Internet, And

644
00:37:56,400 --> 00:38:01,680
Speaker 11: I guess you could say I'm a tech Internet enthusiast, aficionado,

645
00:38:02,000 --> 00:38:03,040
Speaker 11: whatever you want to say.

646
00:38:03,280 --> 00:38:06,200
Speaker 2: I'm excited to talk coffee wife with you. Why do

647
00:38:06,239 --> 00:38:09,000
Speaker 2: you think that people had such a strong emotional reaction

648
00:38:09,200 --> 00:38:10,560
Speaker 2: to coffee Wife.

649
00:38:11,120 --> 00:38:14,600
Speaker 11: Well, one, I think it's absolutely algorithmic, right. I think

650
00:38:14,640 --> 00:38:17,680
Speaker 11: that we know a lot about how algorithms work. I

651
00:38:17,719 --> 00:38:20,440
Speaker 11: think that they absolutely are feeding us and pushing us

652
00:38:20,480 --> 00:38:25,400
Speaker 11: content that is going to elicit strong reactions, emotional reactions

653
00:38:25,400 --> 00:38:27,200
Speaker 11: from us. So even if you don't know this woman,

654
00:38:27,320 --> 00:38:29,799
Speaker 11: don't follow this woman. She wasn't like somebody who had

655
00:38:29,920 --> 00:38:32,400
Speaker 11: a ton of followers. She had a relatively small account.

656
00:38:32,719 --> 00:38:36,600
Speaker 11: Platforms know this is content that it's eliciting strong reaction,

657
00:38:36,800 --> 00:38:39,759
Speaker 11: strong engagement. Let's make sure that more people see it,

658
00:38:40,000 --> 00:38:42,800
Speaker 11: you know, that's the name of the game for platforms. However,

659
00:38:43,400 --> 00:38:46,359
Speaker 11: I do think that the timeframe kind of matters, Like

660
00:38:46,760 --> 00:38:49,560
Speaker 11: I think that this was a time where do you

661
00:38:49,560 --> 00:38:53,080
Speaker 11: remember how in the very beginning of the pandemic we

662
00:38:53,080 --> 00:38:55,000
Speaker 11: were Also there was a sort of novelty to it

663
00:38:55,040 --> 00:38:57,840
Speaker 11: where it was like, who knows what's happening? But then

664
00:38:57,960 --> 00:38:59,680
Speaker 11: that kind of were off, and then it was like, well,

665
00:38:59,719 --> 00:39:01,359
Speaker 11: I guess this is just all of our lives now.

666
00:39:01,680 --> 00:39:04,319
Speaker 11: And I think that this happened at a time when

667
00:39:04,360 --> 00:39:06,680
Speaker 11: a lot of people were just sort of grappling with that.

668
00:39:06,760 --> 00:39:09,200
Speaker 11: I think for me personally, it was a time where

669
00:39:09,239 --> 00:39:11,480
Speaker 11: I was spending way more time than I should have

670
00:39:11,600 --> 00:39:15,399
Speaker 11: been on screens on the internet, really paying a lot

671
00:39:15,400 --> 00:39:17,719
Speaker 11: of attention to what strangers on the Internet were doing,

672
00:39:17,880 --> 00:39:20,040
Speaker 11: because I didn't have a lot going on outside of that, right,

673
00:39:20,080 --> 00:39:21,680
Speaker 11: I wasn't going out the way I used to all

674
00:39:21,719 --> 00:39:25,080
Speaker 11: of that, And I also think we were all feeling

675
00:39:25,440 --> 00:39:30,560
Speaker 11: the sort of like existential dread of how reality feels

676
00:39:30,640 --> 00:39:34,120
Speaker 11: right now. Right, everything is expensive, Rents are rising, Inflation

677
00:39:34,239 --> 00:39:36,880
Speaker 11: is terrible. It just feels like we are being squeezed

678
00:39:36,920 --> 00:39:38,280
Speaker 11: from so many different ankles.

679
00:39:38,480 --> 00:39:40,319
Speaker 3: And so when somebody comes along.

680
00:39:40,040 --> 00:39:44,279
Speaker 11: With just pure the pure joy of a you know,

681
00:39:44,440 --> 00:39:47,080
Speaker 11: having coffee in their garden with their husband every morning,

682
00:39:47,120 --> 00:39:49,960
Speaker 11: and you know, isn't this nice, it's like a trigger

683
00:39:50,239 --> 00:39:52,640
Speaker 11: that It's not surprising to me that it was this

684
00:39:53,160 --> 00:39:54,760
Speaker 11: big tension point for so many people.

685
00:39:55,239 --> 00:39:57,680
Speaker 2: That's so interesting. I think of all the conversations I've

686
00:39:57,719 --> 00:39:59,800
Speaker 2: been having, I'd be curious what you think about that,

687
00:40:00,160 --> 00:40:03,759
Speaker 2: Like how the pandemic sort of warped our relationship to

688
00:40:03,800 --> 00:40:08,120
Speaker 2: the internet and what it looks like trying to sort

689
00:40:08,120 --> 00:40:12,600
Speaker 2: of return to straddling real life and internet life.

690
00:40:12,760 --> 00:40:17,319
Speaker 11: Yeah, boy, do I identify with that and feel you

691
00:40:17,360 --> 00:40:17,680
Speaker 11: on that.

692
00:40:18,120 --> 00:40:20,080
Speaker 3: I mean, I can speak for myself.

693
00:40:20,760 --> 00:40:24,279
Speaker 11: I am not proud of what the pandemic, how I

694
00:40:24,320 --> 00:40:27,759
Speaker 11: responded to the pandemic socially, right, I also am a

695
00:40:27,760 --> 00:40:30,120
Speaker 11: pretty socially anxious person. I'm somebody who's in my head

696
00:40:30,280 --> 00:40:34,200
Speaker 11: a lot, and I'm not proud to say this, but

697
00:40:34,239 --> 00:40:36,000
Speaker 11: I would bet that I'm not the only person who

698
00:40:36,000 --> 00:40:38,759
Speaker 11: feels this way. I think during the pandemic. You know,

699
00:40:38,800 --> 00:40:41,680
Speaker 11: we were watching people die, we were watching people lose

700
00:40:41,719 --> 00:40:44,440
Speaker 11: loved ones, we were watching people lose their livelihoods. It

701
00:40:44,480 --> 00:40:46,880
Speaker 11: was a really tough time, and so it was hard

702
00:40:47,680 --> 00:40:51,279
Speaker 11: for me as somebody who luckily was very privileged, and

703
00:40:51,320 --> 00:40:53,040
Speaker 11: that that wasn't the case for me, right, Like I

704
00:40:53,080 --> 00:40:55,960
Speaker 11: got COVID. People I know got COVID, but thankfully I

705
00:40:56,000 --> 00:40:57,239
Speaker 11: didn't lose my loved ones.

706
00:40:57,600 --> 00:40:59,200
Speaker 3: It wasn't impacting me the way that it was.

707
00:40:59,400 --> 00:41:02,200
Speaker 11: I'm not an essential right, and so I think that

708
00:41:02,719 --> 00:41:08,040
Speaker 11: for me personally, it was strange to deep to grapple

709
00:41:08,160 --> 00:41:11,399
Speaker 11: with that, this feeling of like I am going through

710
00:41:11,440 --> 00:41:14,040
Speaker 11: a tough time and so is everyone. I think it

711
00:41:14,160 --> 00:41:17,920
Speaker 11: for me created this dynamic where I hate to say it,

712
00:41:17,960 --> 00:41:20,040
Speaker 11: but I was very much like what about my pain?

713
00:41:20,200 --> 00:41:22,960
Speaker 11: You know, Like why is like when is it going

714
00:41:23,040 --> 00:41:24,960
Speaker 11: to be my turn for somebody to see me? Like

715
00:41:25,640 --> 00:41:27,920
Speaker 11: I wasn't an essential worker. Nobody around me died, but

716
00:41:27,960 --> 00:41:30,200
Speaker 11: I still had a tough time. I was finding myself

717
00:41:30,200 --> 00:41:36,000
Speaker 11: in this like almost very narcissistic place of wanting somebody

718
00:41:36,040 --> 00:41:38,080
Speaker 11: to acknowledge what I had been through. And so I

719
00:41:38,120 --> 00:41:40,399
Speaker 11: think with Coffee Lady, I think it was a lot

720
00:41:40,400 --> 00:41:46,400
Speaker 11: of people who perhaps were wanting someone to see their pain,

721
00:41:46,600 --> 00:41:49,640
Speaker 11: wanting others to acknowledge their pain and their anxiety and

722
00:41:49,680 --> 00:41:52,040
Speaker 11: their loneliness and their frustration, which is something that I

723
00:41:52,080 --> 00:41:54,959
Speaker 11: can relate to really deeply, and so I think that's

724
00:41:55,280 --> 00:41:57,920
Speaker 11: part of why, because some of the replies that she

725
00:41:58,040 --> 00:42:00,799
Speaker 11: got would be like, I can't afford it, Garden, I

726
00:42:00,840 --> 00:42:03,320
Speaker 11: don't have a husband. You know, I'm alone here, I

727
00:42:03,320 --> 00:42:06,360
Speaker 11: don't have any friends, Like people really making it about

728
00:42:06,760 --> 00:42:10,080
Speaker 11: themselves and what they lack, and like something about that

729
00:42:10,120 --> 00:42:13,360
Speaker 11: tweet I think highlighted the lack that a lot of

730
00:42:13,360 --> 00:42:17,400
Speaker 11: people were feeling. And I just I really, it's easy

731
00:42:17,400 --> 00:42:19,319
Speaker 11: to dunk on these people and be like, Wow, you're

732
00:42:19,360 --> 00:42:22,439
Speaker 11: so dysregulated that that's that this woman, this random woman's

733
00:42:22,480 --> 00:42:23,839
Speaker 11: tweet is making you feel that way.

734
00:42:24,000 --> 00:42:25,279
Speaker 3: But I also kind of get it.

735
00:42:25,440 --> 00:42:26,120
Speaker 9: You're totally right.

736
00:42:26,160 --> 00:42:28,200
Speaker 2: And I know I've been guilty of this in the

737
00:42:28,239 --> 00:42:32,439
Speaker 2: past and probably during the pandemic era Internet, where you're

738
00:42:32,440 --> 00:42:36,799
Speaker 2: taking like your personal pain and I've had moments where

739
00:42:36,840 --> 00:42:38,400
Speaker 2: I'm like, I don't want to see someone happy right

740
00:42:38,400 --> 00:42:41,239
Speaker 2: now because I'm not, And like, I think that there's

741
00:42:41,239 --> 00:42:42,960
Speaker 2: a lot of that, but some of it is sort

742
00:42:43,000 --> 00:42:46,799
Speaker 2: of manifesting as a political statement. I can't quite get

743
00:42:46,840 --> 00:42:49,440
Speaker 2: my head around that phenomenon because I don't want to

744
00:42:49,560 --> 00:42:55,400
Speaker 2: discount the fact that like class rage and class anxiety online.

745
00:42:55,440 --> 00:42:58,960
Speaker 2: I mean, it makes total sense. I experienced it a lot,

746
00:43:00,080 --> 00:43:02,960
Speaker 2: especially it's sort of the further back you go, but

747
00:43:03,040 --> 00:43:06,319
Speaker 2: she's so clearly not the person that can. I think

748
00:43:06,360 --> 00:43:10,200
Speaker 2: it's interesting online when people dogpile on someone who cannot

749
00:43:10,320 --> 00:43:11,520
Speaker 2: help them, right.

750
00:43:12,160 --> 00:43:14,600
Speaker 3: I do think there's a gendered aspect to it.

751
00:43:15,080 --> 00:43:17,480
Speaker 11: I haven't really kind of grappled with this too much

752
00:43:17,640 --> 00:43:20,359
Speaker 11: just yet, but like I know, for me, when I'm

753
00:43:20,400 --> 00:43:25,240
Speaker 11: scrolling TikTok or Instagram, there is something about the visualization

754
00:43:25,320 --> 00:43:27,920
Speaker 11: of a woman who seems like she's got her shit together,

755
00:43:28,000 --> 00:43:30,560
Speaker 11: she's got it all figured out. She wears the perfect

756
00:43:30,640 --> 00:43:34,480
Speaker 11: two piece you know, workout set, she eats right, she

757
00:43:34,760 --> 00:43:37,360
Speaker 11: starts her day with like lemon water or macha instead

758
00:43:37,360 --> 00:43:37,800
Speaker 11: of coffee.

759
00:43:37,840 --> 00:43:38,160
Speaker 3: Whatever.

760
00:43:38,239 --> 00:43:42,240
Speaker 2: It is three gorgeous children who are wealthy act yeah.

761
00:43:42,080 --> 00:43:46,480
Speaker 11: Exactly, And so I think that coffee ladies tweet, at

762
00:43:46,600 --> 00:43:51,760
Speaker 11: least for me, triggered a kind of very gendered, almost

763
00:43:51,800 --> 00:43:55,719
Speaker 11: like politicized anxiety that there are women out there who

764
00:43:55,760 --> 00:43:58,280
Speaker 11: are doing it right and bridget you are doing it wrong,

765
00:43:58,440 --> 00:44:00,759
Speaker 11: like something about like like there has never been a

766
00:44:00,840 --> 00:44:02,480
Speaker 11: day where I'm able to start my day.

767
00:44:03,800 --> 00:44:06,040
Speaker 3: Serenely drinking coffee in my garden.

768
00:44:06,080 --> 00:44:08,040
Speaker 11: I actually do have a small garden, and I never

769
00:44:08,080 --> 00:44:10,440
Speaker 11: start my day out there because I start my day

770
00:44:10,480 --> 00:44:13,880
Speaker 11: like most people, like frazzled late for a call, just

771
00:44:13,920 --> 00:44:16,880
Speaker 11: trying to chug some coffee while I'm getting dressed, like

772
00:44:17,200 --> 00:44:20,120
Speaker 11: doing a million other things. Sure I shouldn't be taking

773
00:44:20,160 --> 00:44:23,640
Speaker 11: a moment smelling the flowers, journaling, YadA, YadA, YadA.

774
00:44:23,440 --> 00:44:25,560
Speaker 2: But yes, gratitude journal exactly.

775
00:44:25,600 --> 00:44:27,279
Speaker 3: But who does that right?

776
00:44:27,320 --> 00:44:30,480
Speaker 11: And so I think there is something where women are

777
00:44:30,520 --> 00:44:32,880
Speaker 11: told that you have to in order to sort of

778
00:44:32,960 --> 00:44:35,400
Speaker 11: signal that you have it together, your mornings have to

779
00:44:35,400 --> 00:44:37,920
Speaker 11: look like X Y Z. And I think that something

780
00:44:37,960 --> 00:44:42,480
Speaker 11: about coffee Lady, something about that tweet signaled to women

781
00:44:42,680 --> 00:44:45,400
Speaker 11: like I've got it all together? Do you feel like

782
00:44:45,440 --> 00:44:47,680
Speaker 11: craft that you don't. I don't think she was. I

783
00:44:47,680 --> 00:44:49,799
Speaker 11: certainly don't think she was trying to do that. But

784
00:44:49,840 --> 00:44:52,040
Speaker 11: that's I think that's probably how it hit some of us.

785
00:44:52,280 --> 00:44:54,040
Speaker 2: The Internet, I think, like a lot of things, is

786
00:44:54,120 --> 00:44:58,080
Speaker 2: sort of built to make women angry at each other. Yes,

787
00:44:58,120 --> 00:45:01,640
Speaker 2: and present each other and yeah, I mean, could you

788
00:45:01,640 --> 00:45:03,200
Speaker 2: speak to that a little bit? I know that that's

789
00:45:03,560 --> 00:45:04,080
Speaker 2: your beat.

790
00:45:04,480 --> 00:45:08,880
Speaker 11: Yes, I mean, it's just a document, a well documented fact.

791
00:45:09,400 --> 00:45:13,320
Speaker 11: Algorithms want women to feel like shit. They want women

792
00:45:13,360 --> 00:45:16,080
Speaker 11: to be comparing themselves to other women, they want women

793
00:45:16,080 --> 00:45:18,240
Speaker 11: to be feeling bad. They want women to be feeling

794
00:45:18,320 --> 00:45:21,520
Speaker 11: like crap all the time. And algorithms and platforms and

795
00:45:21,560 --> 00:45:24,680
Speaker 11: tech leaders make money off of women feeling like shit

796
00:45:24,719 --> 00:45:25,360
Speaker 11: about themselves.

797
00:45:25,360 --> 00:45:26,480
Speaker 3: That's just a fact, right.

798
00:45:26,520 --> 00:45:29,840
Speaker 11: And so if you've ever been scrolling Instagram or TikTok

799
00:45:29,960 --> 00:45:32,759
Speaker 11: or whatever and you keep being surfaced content that makes

800
00:45:32,800 --> 00:45:35,840
Speaker 11: you feel like crap, that's not you. You're not crazy

801
00:45:35,920 --> 00:45:39,960
Speaker 11: or sensitive. Algorithms and platforms do that with intention because

802
00:45:39,960 --> 00:45:42,080
Speaker 11: it keeps you on the platform longer, it keeps you

803
00:45:42,120 --> 00:45:43,920
Speaker 11: coming back, and it makes them money. It is a

804
00:45:44,120 --> 00:45:48,040
Speaker 11: very twisted dynamic that we are a cog in this

805
00:45:48,160 --> 00:45:52,200
Speaker 11: cycle that is making other people, mostly men, rich off

806
00:45:52,239 --> 00:45:55,720
Speaker 11: of our anxiety, off of our fears, off of us.

807
00:45:55,560 --> 00:45:57,040
Speaker 3: Being in competition with each other.

808
00:45:57,360 --> 00:46:00,680
Speaker 11: And rather than like celebrating the ways that we are different,

809
00:46:00,800 --> 00:46:03,120
Speaker 11: celebrating the ways in which like, oh, well, like my

810
00:46:03,239 --> 00:46:05,200
Speaker 11: brand is this, I'm a hot mess, I own it.

811
00:46:05,239 --> 00:46:05,520
Speaker 3: Whatever.

812
00:46:05,560 --> 00:46:08,480
Speaker 11: Whatever algorithms trick us into thinking that all of these

813
00:46:08,640 --> 00:46:11,960
Speaker 11: great things that make us who we are are actually foibles,

814
00:46:12,000 --> 00:46:15,680
Speaker 11: are actually bad And yeah, I mean there's been study

815
00:46:15,719 --> 00:46:18,920
Speaker 11: after study that shows that the more time you spend

816
00:46:19,000 --> 00:46:22,920
Speaker 11: on particularly Instagram, the more young women feel bad about themselves,

817
00:46:22,960 --> 00:46:25,440
Speaker 11: the more body anxiety they have, the more likely they

818
00:46:25,440 --> 00:46:28,480
Speaker 11: are to engage in things like food issues or disordered eating.

819
00:46:28,760 --> 00:46:31,160
Speaker 11: And none of that is by mistake and it's all

820
00:46:31,239 --> 00:46:33,279
Speaker 11: by design. It is a feature, not a bug.

821
00:46:34,640 --> 00:46:38,320
Speaker 2: And that and that would also apply to Coffee Life.

822
00:46:38,480 --> 00:46:40,840
Speaker 2: That people were attacking her as if she was like

823
00:46:40,960 --> 00:46:43,680
Speaker 2: the root cause of it. It was very strange. I

824
00:46:43,719 --> 00:46:45,760
Speaker 2: forget who I was talking to the other day about

825
00:46:46,280 --> 00:46:49,640
Speaker 2: how they felt like they had fucked up their algorithm

826
00:46:50,000 --> 00:46:53,480
Speaker 2: because they said that they weren't interested in something and

827
00:46:53,840 --> 00:46:56,720
Speaker 2: the algorithm kept serving that to them because they cared

828
00:46:56,800 --> 00:46:59,480
Speaker 2: enough to say I'm not interested. And the only way

829
00:46:59,560 --> 00:47:03,640
Speaker 2: to true, truly demonstrate you're not interested is to keep

830
00:47:03,680 --> 00:47:06,879
Speaker 2: scrolling and don't stop. But like if you are, if

831
00:47:06,920 --> 00:47:10,680
Speaker 2: you theoretically you know, see like a coffee wife, TikTok

832
00:47:10,880 --> 00:47:14,160
Speaker 2: come up and you care enough to say I don't

833
00:47:14,280 --> 00:47:17,040
Speaker 2: like this, the algorithm will serve it to you again.

834
00:47:17,080 --> 00:47:20,680
Speaker 2: And so I ran an experiment and it's completely true,

835
00:47:21,080 --> 00:47:23,560
Speaker 2: like that the kind of content I went out of

836
00:47:23,600 --> 00:47:26,480
Speaker 2: my way to say I don't like this. The algorithm

837
00:47:26,520 --> 00:47:29,080
Speaker 2: responds by being like, well, maybe you'll interact with it

838
00:47:29,360 --> 00:47:31,400
Speaker 2: negatively because it makes you feel bad.

839
00:47:31,760 --> 00:47:36,399
Speaker 11: Yes, And so it's so I've experienced the exact same thing.

840
00:47:36,440 --> 00:47:37,480
Speaker 3: I completely agree with you.

841
00:47:37,760 --> 00:47:41,239
Speaker 11: And imagine how harmful that is when it's content that

842
00:47:41,320 --> 00:47:43,680
Speaker 11: you find triggering. Right, when it's content that you have

843
00:47:43,800 --> 00:47:46,080
Speaker 11: identified like that might not be safe or healthy for

844
00:47:46,120 --> 00:47:48,360
Speaker 11: me to see and engage with. Right if the algorithm

845
00:47:48,520 --> 00:47:50,759
Speaker 11: has has gleaned like, oh, she has a little bit

846
00:47:50,800 --> 00:47:53,800
Speaker 11: of an issue with X y Z. Let's keep showing

847
00:47:53,840 --> 00:47:55,200
Speaker 11: it to her and see what happens.

848
00:47:55,760 --> 00:47:56,920
Speaker 3: Yeah, really, that cool.

849
00:47:57,440 --> 00:48:01,680
Speaker 2: The part that's hard is even when I'm looking for it,

850
00:48:01,680 --> 00:48:06,360
Speaker 2: it's hard to escape the like emotional experience of I

851
00:48:06,400 --> 00:48:09,440
Speaker 2: don't want to see that, and like feeling that your

852
00:48:09,480 --> 00:48:12,520
Speaker 2: anger for whatever reason does seem to it routes at

853
00:48:12,560 --> 00:48:16,279
Speaker 2: the person because you can't you know the real kind

854
00:48:16,360 --> 00:48:19,120
Speaker 2: of Yeah, this sounds conspiratorial, but like the real enemy

855
00:48:19,160 --> 00:48:21,919
Speaker 2: has no face right, And so I feel like there

856
00:48:22,000 --> 00:48:24,120
Speaker 2: is this sort of very human instinct to try to

857
00:48:24,440 --> 00:48:28,640
Speaker 2: place a face and a name to what is bothering you,

858
00:48:29,120 --> 00:48:34,120
Speaker 2: when in reality it is something much larger, like you know,

859
00:48:34,200 --> 00:48:37,280
Speaker 2: social media algorithms that are trying to make you upset,

860
00:48:37,680 --> 00:48:42,880
Speaker 2: like the concept of class and like these huge things.

861
00:48:43,200 --> 00:48:46,200
Speaker 2: And it's finding a sort of villain of the day

862
00:48:46,239 --> 00:48:50,320
Speaker 2: to take it out on, even when that person sucks.

863
00:48:50,360 --> 00:48:52,719
Speaker 2: In this case, they didn't, but sometimes they do, but

864
00:48:52,800 --> 00:48:54,840
Speaker 2: it still doesn't it's so unproductive.

865
00:48:55,560 --> 00:48:59,560
Speaker 11: Yeah, we are making a bunch of random people proxies

866
00:48:59,600 --> 00:49:02,280
Speaker 11: for a lot of our very valid anger and pain

867
00:49:02,320 --> 00:49:05,400
Speaker 11: and fear. That's why I always say, like, we're it's

868
00:49:05,440 --> 00:49:07,800
Speaker 11: a game and we're all being played. The only winner

869
00:49:07,840 --> 00:49:10,320
Speaker 11: here are tech platforms and people who run them and

870
00:49:10,320 --> 00:49:12,560
Speaker 11: people who make money from them. And so even if

871
00:49:12,600 --> 00:49:15,480
Speaker 11: you are running a successful little grift for a while,

872
00:49:15,719 --> 00:49:18,839
Speaker 11: engagement mating and all of that, all it takes is

873
00:49:18,880 --> 00:49:21,520
Speaker 11: one algorithmic tweak and then no one's You don't have

874
00:49:21,560 --> 00:49:24,200
Speaker 11: the eyeballs or the attention of the world any longer.

875
00:49:24,239 --> 00:49:27,200
Speaker 11: And so, yeah, it's it's a game, and we're all

876
00:49:27,239 --> 00:49:27,800
Speaker 11: being played.

877
00:49:28,160 --> 00:49:35,040
Speaker 2: What can we What can the collective learn from Coffee Wife.

878
00:49:35,480 --> 00:49:37,759
Speaker 11: Something that I found really interesting about the Coffee Wife

879
00:49:37,760 --> 00:49:40,719
Speaker 11: saga was how everybody assumed she was wealthy because she

880
00:49:40,800 --> 00:49:44,839
Speaker 11: has a garden. And I found that to be really

881
00:49:44,880 --> 00:49:47,319
Speaker 11: interesting because she was like, Oh, it's not like a

882
00:49:47,320 --> 00:49:50,279
Speaker 11: fancy garden, it's just a small garden in my like

883
00:49:50,440 --> 00:49:51,280
Speaker 11: regular home.

884
00:49:52,080 --> 00:49:53,480
Speaker 3: I think that it.

885
00:49:53,480 --> 00:49:56,440
Speaker 11: Is very easy and I say this because I've done

886
00:49:56,440 --> 00:49:59,799
Speaker 11: it to trick yourself into thinking, like, the things that

887
00:49:59,840 --> 00:50:02,480
Speaker 11: I want I can't have. I am, I am, I

888
00:50:02,480 --> 00:50:05,120
Speaker 11: could never have a garden. And I think that that

889
00:50:05,280 --> 00:50:10,680
Speaker 11: really the Coffee Wife thing really showed me that a

890
00:50:10,680 --> 00:50:13,360
Speaker 11: lot of us feel like we can't have things that

891
00:50:13,400 --> 00:50:16,160
Speaker 11: we actually can have. I don't know if that makes sense,

892
00:50:16,480 --> 00:50:18,319
Speaker 11: but the fact that so many people were like, well,

893
00:50:18,400 --> 00:50:19,960
Speaker 11: you have to be rich to have a garden, and

894
00:50:19,960 --> 00:50:22,560
Speaker 11: it's like, well, actually, I don't think that's the case,

895
00:50:22,560 --> 00:50:24,399
Speaker 11: and people who are not rich have gardens all the time,

896
00:50:24,400 --> 00:50:26,920
Speaker 11: And like, why are you assuming that the pastime of

897
00:50:26,960 --> 00:50:29,439
Speaker 11: gardening is something that only the wealthy can do. Even

898
00:50:29,440 --> 00:50:31,000
Speaker 11: if you live in a small apartment, you can still

899
00:50:31,040 --> 00:50:33,520
Speaker 11: have like a window garden or something. I think that

900
00:50:33,760 --> 00:50:35,719
Speaker 11: I think it's easy to trick ourselves into thinking the

901
00:50:35,719 --> 00:50:37,000
Speaker 11: things that we want we cannot have.

902
00:50:37,400 --> 00:50:39,560
Speaker 3: So that's one two.

903
00:50:39,719 --> 00:50:43,360
Speaker 11: I would say, yeah, we really have to be better

904
00:50:44,239 --> 00:50:48,359
Speaker 11: at understanding where we put our pain and who we

905
00:50:48,440 --> 00:50:52,440
Speaker 11: make the proxies for our pain. I would say, if

906
00:50:52,440 --> 00:50:55,799
Speaker 11: the person you are tweeting at cannot change the circumstances

907
00:50:55,800 --> 00:50:58,360
Speaker 11: that you're upset about, maybe you're putting your rage and

908
00:50:58,400 --> 00:51:01,000
Speaker 11: your anger and your emotionality in the wrong place, and

909
00:51:01,000 --> 00:51:04,719
Speaker 11: that we should direct our rage and anger and emotionality

910
00:51:04,880 --> 00:51:05,800
Speaker 11: to the right places.

911
00:51:05,880 --> 00:51:06,040
Speaker 7: Right.

912
00:51:06,360 --> 00:51:09,960
Speaker 11: I know those places tend to be structural and institutional

913
00:51:10,200 --> 00:51:13,840
Speaker 11: and faithless, but we gotta really have a sense of

914
00:51:13,880 --> 00:51:17,120
Speaker 11: what forces are actually making us unhappy, and it's probably

915
00:51:17,120 --> 00:51:18,920
Speaker 11: not this lady drinking coffee in her garden.

916
00:51:20,000 --> 00:51:22,319
Speaker 2: Thank you so much to bridget Todd. Listen to there

917
00:51:22,360 --> 00:51:25,239
Speaker 2: are no girls on the internet every single week, I

918
00:51:25,280 --> 00:51:31,040
Speaker 2: sure do. So what became of our coffee wife legend?

919
00:51:31,640 --> 00:51:34,600
Speaker 2: Daisy didn't respond to my request for an interview, and

920
00:51:34,760 --> 00:51:37,360
Speaker 2: I respect that she just wants to be a person

921
00:51:37,520 --> 00:51:41,080
Speaker 2: who does pleasant things with people she likes. Some people

922
00:51:41,239 --> 00:51:44,680
Speaker 2: just don't want a dumb bitch podcaster interfering with their life,

923
00:51:44,719 --> 00:51:47,359
Speaker 2: and I have to accept that as far as her

924
00:51:47,400 --> 00:51:52,279
Speaker 2: online persona, Daisy is no longer Coffee Wife. She is

925
00:51:52,360 --> 00:51:55,560
Speaker 2: Daisy and appears to be spending her time generally not

926
00:51:55,800 --> 00:51:59,640
Speaker 2: on Twitter nowadays. She lives in Bali, India, and is

927
00:51:59,680 --> 00:52:03,040
Speaker 2: returning to her lashes business later in the year. I

928
00:52:03,120 --> 00:52:06,560
Speaker 2: have no idea if she's a wife, if she drinks coffee,

929
00:52:06,719 --> 00:52:10,759
Speaker 2: but she's certainly Daisy, and I like Daisy, and with

930
00:52:10,840 --> 00:52:21,440
Speaker 2: that the coffee wife. Your sixteenth minute ends. Now, Okay,

931
00:52:22,520 --> 00:52:26,000
Speaker 2: I'm on the couch with my boyfriend drinking coffee. Close enough.

932
00:52:27,120 --> 00:52:28,000
Speaker 5: Oh I should I guess it?

933
00:52:28,040 --> 00:52:29,359
Speaker 6: Should hold I should hold it.

934
00:52:29,400 --> 00:52:30,480
Speaker 3: You're right, get your coffee.

935
00:52:30,560 --> 00:52:33,279
Speaker 5: Yeah, but hey, coffee in the morning, even after I've

936
00:52:33,320 --> 00:52:36,200
Speaker 5: gotten off my damn shift, coffee with my wife.

937
00:52:38,440 --> 00:52:40,880
Speaker 9: And we don't have a garden. We do have a.

938
00:52:42,520 --> 00:52:45,200
Speaker 3: Little deck, but I just kind of we have.

939
00:52:45,160 --> 00:52:49,880
Speaker 5: A bug in the house though, Casper, Casper, two.

940
00:52:49,760 --> 00:52:51,440
Speaker 9: Bugs, we do, two bugs.

941
00:52:51,480 --> 00:52:53,680
Speaker 8: I just the deck kind of stresses me out because

942
00:52:53,680 --> 00:52:55,920
Speaker 8: there's so much pollution. Who we're across the street from

943
00:52:55,960 --> 00:52:58,239
Speaker 8: a We shouldn't say where we.

944
00:52:58,239 --> 00:53:01,200
Speaker 5: Are, No, we should, but you can visualize the pollution

945
00:53:01,239 --> 00:53:02,320
Speaker 5: because we can see.

946
00:53:02,080 --> 00:53:03,279
Speaker 4: All of the gathering dust.

947
00:53:03,440 --> 00:53:05,560
Speaker 5: Just so much dust the accumulated ducks.

948
00:53:05,719 --> 00:53:08,399
Speaker 2: So you just walked up to Casper and started kissing him.

949
00:53:08,560 --> 00:53:13,040
Speaker 5: They are, they're kissing right now, and there's looking Casper's forehead.

950
00:53:13,640 --> 00:53:16,879
Speaker 2: You love saying you're so dirty, You're so dirty. They're

951
00:53:16,920 --> 00:53:17,680
Speaker 2: the same size.

952
00:53:17,680 --> 00:53:17,839
Speaker 10: Now.

953
00:53:17,880 --> 00:53:18,319
Speaker 3: It's great.

954
00:53:20,480 --> 00:53:22,600
Speaker 5: We could try this in a garden at some point though,

955
00:53:22,680 --> 00:53:23,239
Speaker 5: don't you think.

956
00:53:28,719 --> 00:53:32,320
Speaker 2: Sixteenth Minute is a production of Cool Zone Media and iHeartRadio.

957
00:53:32,880 --> 00:53:36,160
Speaker 2: It is written, posted, and produced by me Jamie Loftus.

958
00:53:36,360 --> 00:53:39,719
Speaker 2: Our executive producers are Sophie Lichtterman and Robert Evans. The

959
00:53:39,800 --> 00:53:43,800
Speaker 2: amazing Ian Johnson is our supervising producer and our editor.

960
00:53:44,200 --> 00:53:47,960
Speaker 2: Our theme song is by Sad thirteen. Special thanks to

961
00:53:48,080 --> 00:53:51,720
Speaker 2: Grant Creator and Sophie Lichterman for doing voiceover and pet

962
00:53:51,719 --> 00:53:54,760
Speaker 2: shout outs to our dog producer Anderson my cat's fleeing

963
00:53:54,800 --> 00:53:57,560
Speaker 2: Casper and by pet Rothbert who will outload us all.

964
00:53:58,040 --> 00:54:01,040
Speaker 2: Bye b