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Speaker 1: There Are No Girls on the Internet. As a production

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

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Speaker 1: is there are No Girls on the Internet. Something that

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Speaker 1: should surprise nobody in America is that school only recently

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Speaker 1: just started back and already. There was a school shooting

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Speaker 1: at a Catholic school in Minneapolis, Minnesota, last week that

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Speaker 1: left an eight year old and a ten year old

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Speaker 1: dead and injured seventeen others. According to the Minneapolis Police

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Speaker 1: Chief Brian O'Haras, the three weapons used in the attack

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Speaker 1: were purchased legally. Police official said, Now, I wanted to

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Speaker 1: talk about this shooting with my producer Joey. Joey, thank

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Speaker 1: you so much for being here.

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Speaker 2: Hey, thanks for having me on Bridget, you know, regardless

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Speaker 2: of it being sort of a lesson, uh not so

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Speaker 2: great topic today.

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Speaker 1: Yeah, and it's kind of coincidental because you and I

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Speaker 1: had been working on an episode about the way trans

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Speaker 1: people are constantly and unfairly blamed for tragedies or mass

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Speaker 1: shootings or mass acts of violence online before all the

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Speaker 1: details are even really clear. And so I was offline

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Speaker 1: when this shooting happened, and a friend pined to me

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Speaker 1: and said, oh, look at this school shooting. It looks

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Speaker 1: like the shooter was trands. And I said, oh, I'm

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Speaker 1: very online, I know what's going on here. You know,

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Speaker 1: this is a familiar trope to me. It's a thing

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Speaker 1: that happens after a mass shooting online, the internet circulates

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Speaker 1: to say that the suspect is trans and it turned

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Speaker 1: out when the when the when more information came in

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Speaker 1: that this suspect actually was trans. Yeah.

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Speaker 3: I had kind of a similar experience where one of

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Speaker 3: my good friends works in you know, broadcast news, and

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Speaker 3: she had texted me and was like, well, she'd kind

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Speaker 3: of she texted like you know, our group chat and

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Speaker 3: was like this happened. That was the first lie I

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Speaker 3: had heard of it, and was like, oh, the shooter's trans.

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Speaker 3: And my immediate response was oh, well, like are they sure,

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Speaker 3: because like they say this every time, so like I

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Speaker 3: don't know, and she was like no, I'm literally looking

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Speaker 3: at like the name change document right now.

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Speaker 1: And I was like, oh, well that's a twist.

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Speaker 3: I guess if you say it enough times, it will

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Speaker 3: happen again. Like you said, coincidental timing, I think, like

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Speaker 3: obviously what happened.

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Speaker 1: This is like terrible.

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Speaker 3: And even backtracking a little bit, something I was thinking

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Speaker 3: about this morning or like when we were planning this

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Speaker 3: episode was the fact that even when I kind of

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Speaker 3: first heard like, oh, there was this shooting that happened,

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Speaker 3: something that really I think struck me was the fact

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Speaker 3: that I was like, it was almost the fact that

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Speaker 3: I didn't even really feel like I had a response,

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Speaker 3: Like I was kind of just like, oh, another shooting, okay,

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Speaker 3: Like this is so standard at this point, it's like

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Speaker 3: really disappointing to see how much it's like I almost

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Speaker 3: kind of felt like I was like expecting this, you know,

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Speaker 3: like this happened so frequently at this point, it like

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Speaker 3: barely even like registered.

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Speaker 4: But yeah, obviously this kind of complicates the situation.

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Speaker 1: And you know, glad we're talking about it.

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Speaker 4: If anything.

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Speaker 1: Yeah, so here's what we know about the shooter, Robin Westman,

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Speaker 1: who police said died of a self and inflicted gunshot

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Speaker 1: wound in the church parking lot after the shooting. I've

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Speaker 1: seen it reported as a manifesto, but I would not

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Speaker 1: describe a document like that using the word manifesto because

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Speaker 1: I think it gives the wrong connotation. I think it's

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Speaker 1: kind of like what people like this might want. But

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Speaker 1: even in that regard, when I looked at what they

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Speaker 1: were calling a manifesto, it really is sort of stream

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Speaker 1: of consciousness videos and writings where she definitely fixates on violence,

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Speaker 1: a real obsession with school shooters and guns.

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Speaker 5: Right.

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Speaker 1: But even in her writing she says things like, there

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Speaker 1: is no message, and this is not about religion. It

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Speaker 1: is certainly not the kind of online presence, and I

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Speaker 1: think that anyone can really use to paint a clear

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Speaker 1: portrait of a motive other than and this is clearly

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Speaker 1: a disturbed person who at times references the fact that

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Speaker 1: she knows she is disturbed, like she knows she has

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Speaker 1: these issues. She talks about how I grew up in

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Speaker 1: a good family with a good support system, and yet

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Speaker 1: in every situation I've ever been in, every school, and

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Speaker 1: every job I've ever been in, I've had these kinds

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Speaker 1: of dark fantasies, right, And so I it's we don't

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Speaker 1: really have a lot of clarity on motive Jesse yet.

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Speaker 1: But what we do know is that as a seventeen

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Speaker 1: year old, Westman filed a Cork document to change her

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Speaker 1: first name to Robin. The document says that Westman quote

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Speaker 1: identified as female and wants her name to reflect that identification.

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Speaker 3: I also heard this morning that I guess they're also

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Speaker 3: in her journal or in the shooters journals.

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Speaker 4: There's maybe some evidence that this is somebody who was considering.

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Speaker 3: De transitioning or like maybe identifies differently now, which again

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Speaker 3: I think kind of like further complicates this where it's like,

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Speaker 3: you know, obviously like we're going to have to talk

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Speaker 3: about the fact that she identified it trans at some point,

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Speaker 3: but kind of almost going back to what you said

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Speaker 3: about the like streatment of conscious videos and a lot

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Speaker 3: of the other stuff that has come out about like

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Speaker 3: her like fixation on school shooters and stuff like that.

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Speaker 4: Like there's so much other things going on that very.

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Speaker 3: Clearly I have more to do with the actual motive

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Speaker 3: than whether or not this person is trans. But yeah,

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Speaker 3: it does appear that at some point she did identify

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Speaker 3: as female, she did change that to change her name

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Speaker 3: and gender marker in.

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Speaker 1: Some cases to reflect that. So that's really good context

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Speaker 1: and I think adds credence to my sort of overall

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Speaker 1: point about this is that this just happened. You know,

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Speaker 1: you and I are recording on Friday, August twenty ninth.

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Speaker 1: This just happened, and I think as investigators do their jobs,

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Speaker 1: more will become clear. We might get more information, But

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Speaker 1: I think it's the online rush to zero in on

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Speaker 1: this one part of this person's identity, to say and

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Speaker 1: that's why she this thing. And I mean, I know

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Speaker 1: the people who are doing that are doing it with intention,

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Speaker 1: so I'm not telling them, I'm not saying anything. I

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Speaker 1: would say that they don't already know what they're doing.

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Speaker 1: But it just goes to show how we can't have

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Speaker 1: a full conversation about what's happening with this tragedy. Two

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Speaker 1: kids are dead, and I think that we owe it

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Speaker 1: to those kids and their communities and their families and

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Speaker 1: people who love them to have a full accounting of

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Speaker 1: what happened here, not just zeroing in on one tidy,

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Speaker 1: convenient narrative, which it sounds like even that narrative is

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Speaker 1: more complicated than then the people who are boosting it

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Speaker 1: would have you believe, right.

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Speaker 3: And it's like every time this happens, there's always, you know,

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Speaker 3: the conversation about gun regulation and how like in gun

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Speaker 3: violence and gun culture, and that also is also like

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Speaker 3: always immediately like no, no, no, no, we can't talk about that,

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Speaker 3: And it's like interesting that it's like, of all of

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Speaker 3: the things that it aspects of this conversation that we

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Speaker 3: should be happening, we're gonna end up having to dedicate

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Speaker 3: so much unnecessary airtime to the fact that this person

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Speaker 3: identified as trans at one point maybe still did again.

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Speaker 4: Yeah, still, story is still developing.

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Speaker 3: This is something that I read like literally a couple

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Speaker 3: hours ago.

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Speaker 1: So who's to say, well now in a week.

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Speaker 3: But yeah, there's just there's so many different elements here,

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Speaker 3: and I feel like I want to emphasize the point

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Speaker 3: that it's like we're talking about the fact that she

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Speaker 3: may or may not have been trans because we're kind of.

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Speaker 1: Forced to have that conversation. That is a great way

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Speaker 1: to put it. We're forced to have that conversation and

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Speaker 1: not have conversations about all that. I mean, a good

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Speaker 1: place to start might be gun regulation. I don't know what. No,

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Speaker 1: And so the mayor of Minneapolis has been urging the

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Speaker 1: public to avoid scapegoating trans folks in the wake of

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Speaker 1: this tragedy. The mayor said, quote, I've heard a whole

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Speaker 1: lot of hate directed at our trans community. Anybody that

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Speaker 1: is using this as an opportunity to villainize our trans

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Speaker 1: community or any other community out there, has a lot

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Speaker 1: lot their sense of common humanity. We should not be

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Speaker 1: operating out of the place of hate for anyone. We

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Speaker 1: should be operating out of a place of love for

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Speaker 1: kids kids died today. This needs to be about them,

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Speaker 1: and so kind of like what you were saying, Joey,

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Speaker 1: it is unfortunate that the shooter's identity has been thrust

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Speaker 1: in the forefront in this way to the point where

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Speaker 1: we need to be even making this episode kind of

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Speaker 1: debunking the way that people on the right online have

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Speaker 1: been talking about this, because it really obscures the fact

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Speaker 1: that these kids who were you know, pad parents who

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Speaker 1: loved them, are part of a community that loved them,

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Speaker 1: that this should be about them. But because of the

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Speaker 1: way that extremists have talked about this shooting and amplified

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Speaker 1: narratives about this shooting and amplified narratives about other incidents

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Speaker 1: in the past it had nothing to do with trans people,

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Speaker 1: we are kind of forced to be debunking this idea

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Speaker 1: about sort of trans terror, and so according to police,

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Speaker 1: we don't even really know much yet today when we're

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Speaker 1: recording this about the motive, but that does not stop

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Speaker 1: the FBI. I'm labeling the shooting as both an act

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Speaker 1: of terrorism and a hate crime against Catholics, and in

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Speaker 1: like extremist mega online circles on social media, the term

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Speaker 1: that they are circulating is the deepest of air quotes

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Speaker 1: on this one, trans terrorism. And I've heard other iterations

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Speaker 1: of it like trans tifa. Essentially this false idea that

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Speaker 1: trans people are more likely to commit public acts of

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Speaker 1: violence that is constantly repeated online. Have you seen it?

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Speaker 3: I have, but trans tifa. This is the first I'm

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Speaker 3: hearing of trans tifa. Okay, I actually know.

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Speaker 4: I was about to be like, I do believe the

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Speaker 4: trans community could have come up.

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Speaker 3: With a better name than that, but actually I'm not

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Speaker 3: sure about that.

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Speaker 1: Trans tifa though, that is okay, God, I'm.

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Speaker 3: Looking on what it was specifically that said this, but

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Speaker 3: it was like some right wing figure. They literally said

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Speaker 3: something where they were like the trans terrorism that's like

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Speaker 3: the most dangerous homegrown terrorism right now. And I was like,

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Speaker 3: I'm so sorry. Have you met like a single trance?

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Speaker 3: I mean, obviously not, because you wouldn't be saying this

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Speaker 3: shit if you had.

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Speaker 1: But I was like, the idea of like.

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Speaker 3: This transshadow terrorist group that's operating in this country. Like,

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Speaker 3: what the hell are you talking about? I don't know,

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Speaker 3: It's it's ridiculous. Every barista in this country is actually

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Speaker 3: a sleeper agent.

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Speaker 1: Yeah, I mean the in their fantasy, every barista maybe

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Speaker 1: like everybody with blue hair or something is. Yeah, it's

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Speaker 1: like a sleep a sleeper agent that is just one

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Speaker 1: bad tip away from going full joker or something. Truly,

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Speaker 1: that is how people talk about the trans community online.

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Speaker 1: I'm sorry, I think you've mean the woker.

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Speaker 3: I really want to take this seriously and not make

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Speaker 3: jokes about this, but I was reading through so.

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Speaker 1: Much about this and I was like, oh God, like,

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Speaker 1: this is where we're at. This is where we're at,

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Speaker 1: this is the Yeah. So none of this, I mean,

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Speaker 1: I don't need to tell you, none of this is new.

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Speaker 1: According to a report from GLAD, social media accounts with

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Speaker 1: a clear history of anti trans rhetoric frequently and importantly

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Speaker 1: falsely accused trans people of crimes, particularly mass shooting events,

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Speaker 1: before facts are known, and so just like in this case,

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Speaker 1: the day that the shooting happened, people were already circulating

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Speaker 1: this sort of trans terror claim. But the fact is

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Speaker 1: there is no evidence of escalating violence committed by LGBTQ people,

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Speaker 1: and extremism and domestic terrorism experts told PolitiFact there is

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Speaker 1: no widespread threat of growing radicalization or violence from the

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Speaker 1: trans population. Now. Accusing folks from a small and likely

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Speaker 1: vulnerable community of being responsible for mass shootings is just

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Speaker 1: clearly like you're trying to humanize them, other them, demonize them,

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Speaker 1: and generally promote fear around trans folks and then binary folks.

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Speaker 1: And I think the important thing for folks to note

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Speaker 1: is that we're talking about a situation where the shooter

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Speaker 1: it sounds like, identified as trans at one point or another.

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Speaker 1: Oftentimes this happens whether or not a trans person had

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Speaker 1: anything to do with it at all.

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Speaker 3: Yeah, this was also making me think about, I mean again,

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Speaker 3: before kind of learning this, now, I aspect that maybe

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Speaker 3: they now don't identify as trans. Before learning that, I

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Speaker 3: was thinking about the fact that it's like the problem

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Speaker 3: with so much of this like just idiotic misinformation or

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Speaker 3: around trans people, around queer people, around gay people, is

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Speaker 3: that like there's always going to be the one person

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Speaker 3: that amplifies that thing.

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Speaker 4: Like I was talking to a friend recently about like.

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Speaker 1: All of the you know, when right wing weirdos want.

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Speaker 3: To be like, oh yeah, gay people are all like

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Speaker 3: pedophiles or all predators, and it's like okay, and then

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Speaker 3: you can find like the one person to point to

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Speaker 3: to be like they're like there was a like director

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Speaker 3: we were talking about where we were like, oh yeah,

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Speaker 3: remember like they came out and then it immediately was

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Speaker 3: revealed that they were like a pedophile and all of

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Speaker 3: this shit, and it was like it sucks because you're

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Speaker 3: always going to be able to find the one person.

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Speaker 3: But then at the same time, it's like right, because

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Speaker 3: people are just people, and they're shitty people no matter

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Speaker 3: what you identify as like for that one, like, there's

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Speaker 3: also a bazillion like straight people that are pedophiles or

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Speaker 3: straight people that are going.

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Speaker 1: To do mass shootings.

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Speaker 3: When you look at the actual numbers, most you know,

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Speaker 3: mass shooters, most school shooters, they are white, cis heterosexual men,

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Speaker 3: so like, but yeah, but the problem is like at

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Speaker 3: the end of the day, you're always going to be

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Speaker 3: able to find like the one person that is like

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Speaker 3: doing the really bad thing. And you know, it's easy

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Speaker 3: for if you're trying to demonize your people point to

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Speaker 3: that one person as like representative of an entire group.

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Speaker 4: This happens for literally every marginalized group.

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Speaker 3: You know, this is like what's at the root of

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Speaker 3: like you know, onophobia and racism, and you could always

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Speaker 3: find the one person to be like see that, that

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Speaker 3: is what the problem is. And I think that is

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Speaker 3: like the thing that makes me nervous about this.

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Speaker 1: Absolutely I was thinking the same thing, but you put

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Speaker 1: that so well because I definitely feel this as a

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Speaker 1: black person, where I have to be the representative of

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Speaker 1: black people everywhere, right, and so it is dehumanization and

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Speaker 1: that it's what you are not judged by what you

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Speaker 1: do your behavior. You are judged and scrutinized by the

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Speaker 1: behavior of others. And so you know. And it's interesting

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Speaker 1: to me because as the research shows, and we'll talk

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Speaker 1: about it in a moment, but the researchers could not

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Speaker 1: be clear that the majority of mass shootings are, as

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Speaker 1: you said, perpetrated by white CIS men. That is just

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Speaker 1: a fact. And I don't think we have a culture

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Speaker 1: that demands that white men writ large need to answer

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Speaker 1: for the behavior of the men who are largely behind

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Speaker 1: these instances of mass violence. Yet I think that when

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Speaker 1: you when you do have, you know, one off marginalized

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Speaker 1: people who unfortunately do things like this, the entire group

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Speaker 1: is judged by those one off people's actions and behavior.

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Speaker 1: Does that make sense? Yeah?

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Speaker 3: Absolutely, I mean it's it's when you have any sort

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Speaker 3: of marginalized identity, you're always not seen as an individual.

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Speaker 3: You are seen as a representative of that group versus

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Speaker 3: like if you are obviously if you're a cis white man,

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Speaker 3: but honestly, like anybody, like I'm somebody who like I'm white,

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Speaker 3: if I do something stupid, nobody's going to be like, see,

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Speaker 3: this is.

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Speaker 4: Proof that like white people are like that.

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Speaker 3: As a trans person, if I do something stupid, that

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Speaker 3: will probably be seen as, oh see, y'all are crazy.

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Speaker 3: But it's like yeah, Like it is like if you

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Speaker 3: have any sort of marginalized identity, you are kind of

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Speaker 3: seen as exemplifying that community, where if you are part

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Speaker 3: of the kind of more privileged side of that, you

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Speaker 3: don't experience that you are seen as an individu Well,

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Speaker 3: you're seen as you know, these like lone wolf shooters

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Speaker 3: that nobody knows why it happened.

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Speaker 1: Again, it feels like I feel like I've.

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Speaker 3: Had this conversation so many times because it's like it

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Speaker 3: is the same story. I think it's just like right

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Speaker 3: now it is, we're having this again, because this really

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Speaker 3: is one of the first really prominent stories where it

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Speaker 3: has been like a trans person that is bet at

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Speaker 3: the center of this.

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Speaker 1: And the point I want to make about this is

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Speaker 1: that this is identity based disinformation. It might not look

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Speaker 1: like it, it might not be the kind of thing

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Speaker 1: that traditionally disinformation researchers would call out as disinformation, but

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Speaker 1: the way that trans people are baselessly blamed and connected

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Speaker 1: to tragedies, mass shootings, instances of mass violence, that is

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Speaker 1: to me identity based disinformation. And I see it over

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Speaker 1: and over again. And I would be willing to bet

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Speaker 1: that if you spend any time on social media, you

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Speaker 1: have probably seen this kind of thing play out online already,

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Speaker 1: because there is a particular image that I can see

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Speaker 1: it in my head of a kind of person with blonde,

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Speaker 1: shaggy hair holding a rifle that often circulates online claiming

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Speaker 1: that it shows the perpetrator of whenever there's a shooting

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Speaker 1: or a tragedy or an instance of mass violence, and

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Speaker 1: it claims to show this person who they the comment

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Speaker 1: say is trans, but it is actually a very well

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Speaker 1: worn image to the point that it's almost a meme.

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Speaker 1: It's an image of this guy, Sam Hyde, who is

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Speaker 1: an extremist comedian and YouTuber. He has his We can

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Speaker 1: do a whole episode on him. He there's a lot

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Speaker 1: to say about him, but let's just that's who it is.

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Speaker 3: Kind of also, like taking a wider look at this issue,

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Speaker 3: I do think it's really interesting that that photo is

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Speaker 3: a cisman. Yeah, because like I've seen that photo million

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Speaker 3: times too, and I'll be real, like I always kind

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Speaker 3: of just assumed it was some random trans person until

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Speaker 3: like listening to the episode that you did with stuff

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Speaker 3: Mom never told you about this where you talked about

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Speaker 3: this same image, and I think it just goes to

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Speaker 3: show again, like taking a sort of wider look at

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Speaker 3: what happens when this sort of transphobic rhetoric becomes so normalized.

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Speaker 3: Is it's like, oh, you see somebody with long hair,

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Speaker 3: and you're immediately going to be like it.

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Speaker 4: Is narrowing the gender roles again.

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Speaker 3: Like if you were looking at all of this through

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Speaker 3: like a very transphobic lens, it's like, yeah, you're we're

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Speaker 3: going back to these like very very strict gender roles,

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Speaker 3: where like you can have a CIS ban with long

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Speaker 3: hair and use that image to be like, see they're

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Speaker 3: trans or they you know, the way that these people

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Speaker 3: are going to say it is going to be like

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Speaker 3: they think they're a woman or whatever. I'm not saying

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Speaker 3: that I agree with that rhetoric, but it's like, I

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Speaker 3: don't know, I find it kind of sis people.

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Speaker 1: I think, like, if you want to.

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Speaker 3: Make it by yourselves, if you really want to like

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Speaker 3: not have to human out whatever, like, think about the

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Speaker 3: fact that it's like all of this bad rhetoric is

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Speaker 3: going to come back to just make gender roles more

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Speaker 3: strict and more restrictive and just bad for everybody, regardless

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Speaker 3: of you know, whether you're trans or SIS or whatever.

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Speaker 1: Don't even get me started on this because this is

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Speaker 1: the drum that I beat. This is a tangent, but

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Speaker 1: it's a drum that I beat all the time. So,

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Speaker 1: as you said, if you are someone who doesn't give

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Speaker 1: a fuck about the humanity of trans people and you're like,

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Speaker 1: I only care about me and that's that's your orientation, fine, Okay,

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Speaker 1: I don't sh have that orientation, but got you when

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Speaker 1: you get into a place where you are so strictly

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Speaker 1: policing the gender of other people along this very narrow

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Speaker 1: understanding of gender, that shit always comes back.

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Speaker 4: Around, right exactly.

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Speaker 1: It is especially disappointing to me when I see this

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Speaker 1: from other Black CIS women who will say like, oh,

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Speaker 1: well you know where they will say, they will say

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Speaker 1: things that are very transphobic, and I always think, like,

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Speaker 1: nobody who is CIS gender gets transphobically compared to men,

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Speaker 1: like black CIS women. That is like when you want

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Speaker 1: to when people wanted to insult Michelle Obama, that go

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Speaker 1: to insult was, oh, she's really a man. She looks

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Speaker 1: like a man. Da da da da. If you can't

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Speaker 1: see the clear line from policing the gender of other

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Speaker 1: people to that shit coming back around to you, I

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Speaker 1: don't know what to tell you. And so if you're

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Speaker 1: someone who doesn't care about the humanity of trans folks

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Speaker 1: and are only caring about yourself when you I mean,

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Speaker 1: it's like Beyonce said, when you play me, you play

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Speaker 1: yourself when you when you play those games, it comes

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Speaker 1: back around to us. And so exactly, I just have

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Speaker 1: to say that like it is. It especially hurts coming

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Speaker 1: from other sis black women, because I just know that,

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Speaker 1: like our gender is so scrutinized, the way the way

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Speaker 1: that the whatever we've got going on with gender wherever

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Speaker 1: we're at, that is so scrutinized, And it's like, why

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Speaker 1: would you want to participate in that kind of climate

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Speaker 1: for somebody else when like when you like, you know

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Speaker 1: what I'm saying, it's just yes, I'll move on.

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Speaker 6: Yeah, No, absolutely, though I mean it's yeah, and I yeah,

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Speaker 6: not to go on too much of a handship, but

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Speaker 6: like literally every issue where like transphopia is through the

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Speaker 6: conversation about sports right now, and like trans people's participation

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Speaker 6: in sports, it's like that is maybe the most obvious

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Speaker 6: way we're seeing it come background and like also hurt

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Speaker 6: sist people.

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Speaker 3: But it's like, yeah, like just just because you're going

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Speaker 3: after us as like your top target, like y'all are next. Yes,

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Speaker 3: if we get to the point where we're starting to

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Speaker 3: police people's gender like this, it's not gonna stop because

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Speaker 3: it hasn't. We've seen this, like we've been seeing this

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Speaker 3: for years now, and it's insane. We're at the point

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Speaker 3: where like, yeah, again, there was that story a couple

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Speaker 3: weeks ago about like a CIS woman who like was

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Speaker 3: being sexually her breast and like a buffalo wild wings

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Speaker 3: bathroom because the like serverir didn't believe that she was

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Speaker 3: like quote unquote really a woman, and like it was like, Yeah,

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Speaker 3: this should be a wake up call to the rest

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Speaker 3: of you if you really, like do not care about us,

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Speaker 3: at least care about yourselves.

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Speaker 1: I don't know.

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Speaker 5: Let's take a quick break at our back.

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Speaker 1: So we're talking about what happens when trans people are

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Speaker 1: baselessly blamed for instances of mass violence or tragedy online.

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Speaker 1: So in twenty twenty three, a fact checker and journalist

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Speaker 1: named Bill McCarthy described that whenever he sees a mass shooting,

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Speaker 1: his heart does not just sink for the victims and

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Speaker 1: their families and their communities, but it also sinks because

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Speaker 1: he knows that other completely blameless people will be falsely

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Speaker 1: accused of being the killer, with their pictures splashed all

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Speaker 1: over the internet. In a piece called mass Shootings the

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Speaker 1: Other Innocent Victims, McCarthy really shed light into this where

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Speaker 1: after a mass shooting in Nashville, that picture of Sam Hyde,

436
00:22:40,760 --> 00:22:44,480
Speaker 1: who is not trans, was misidentified as both being the

437
00:22:44,520 --> 00:22:48,439
Speaker 1: perpetrator and trans McCarthy writes, shortly after police said they

438
00:22:48,440 --> 00:22:50,359
Speaker 1: responded to a shooting, I opened Twitter and ran a

439
00:22:50,400 --> 00:22:55,120
Speaker 1: simple keyword search Nashville shooter identified. According to dozens of results,

440
00:22:55,240 --> 00:22:57,679
Speaker 1: the city's officials had already sing a lot of perpetrator.

441
00:22:57,880 --> 00:23:00,840
Speaker 1: It was a trans woman named Samantha Hyde. Post claim.

442
00:23:00,960 --> 00:23:03,600
Speaker 1: Now that image at this point it's I mean, I

443
00:23:03,840 --> 00:23:05,720
Speaker 1: think of it as a meme, but like it actually

444
00:23:05,720 --> 00:23:08,240
Speaker 1: did originate as a meme on four Chan. So when

445
00:23:08,240 --> 00:23:11,040
Speaker 1: a shooting happens, or a tragedy happens, it's like a

446
00:23:11,080 --> 00:23:14,400
Speaker 1: meme to circulate this image of sam Hyde and say

447
00:23:14,400 --> 00:23:17,480
Speaker 1: that it's a suspect and that they're trans. Internet users

448
00:23:17,480 --> 00:23:20,240
Speaker 1: have been trying to trick people into believing that Hyde

449
00:23:20,320 --> 00:23:24,240
Speaker 1: was behind so many tragedies over the years. There was

450
00:23:24,280 --> 00:23:26,520
Speaker 1: also an attempt in that Nashville shooting to pin the

451
00:23:26,560 --> 00:23:30,200
Speaker 1: attack on Clara Sorrenti, a transactivist and video game streamer

452
00:23:30,240 --> 00:23:32,800
Speaker 1: that people might know as Kepple's who folks might recall

453
00:23:32,840 --> 00:23:34,280
Speaker 1: we did an episode on this kind of a while

454
00:23:34,280 --> 00:23:37,880
Speaker 1: Ago was forced to flee her Canada home after being

455
00:23:37,920 --> 00:23:41,760
Speaker 1: targeted by an online harassment campaign. It's not just Nashville.

456
00:23:41,800 --> 00:23:45,080
Speaker 1: After the After the Uvaldi shooting in Texas, this photo

457
00:23:45,119 --> 00:23:48,240
Speaker 1: of an actual trans woman named Sam So, not the

458
00:23:48,280 --> 00:23:52,399
Speaker 1: CIS comedian named Sam Different. Sam actual trans woman, was

459
00:23:52,400 --> 00:23:55,399
Speaker 1: circulated on social media, claiming that she was the perpetrator.

460
00:23:55,600 --> 00:23:58,800
Speaker 1: She had to actually post an image of herself saying like, hey,

461
00:23:58,920 --> 00:24:00,800
Speaker 1: I am alive because the sh shooter in that attack

462
00:24:00,880 --> 00:24:03,760
Speaker 1: was killed by police. And you know, I have to say, like,

463
00:24:03,840 --> 00:24:06,280
Speaker 1: I've never even been to Texas. I live in Georgia.

464
00:24:06,359 --> 00:24:09,960
Speaker 1: I mean, the way that people have to prove to

465
00:24:10,600 --> 00:24:13,640
Speaker 1: strangers on the Internet that they're not involved in these

466
00:24:13,720 --> 00:24:16,359
Speaker 1: crimes when they had nothing to do with it. I mean,

467
00:24:16,400 --> 00:24:18,119
Speaker 1: I just can't imagine what that would be like. But

468
00:24:18,560 --> 00:24:22,080
Speaker 1: that has not stopped these claims from going viral, from

469
00:24:22,160 --> 00:24:25,240
Speaker 1: harming innocent trans people and then also just creating this

470
00:24:25,400 --> 00:24:29,439
Speaker 1: false idea, I would say, intentionally so that trans people

471
00:24:29,520 --> 00:24:32,080
Speaker 1: are linked to violence and are dangerous.

472
00:24:32,680 --> 00:24:34,439
Speaker 3: Yeah, I mean, like you said again, it's all just

473
00:24:34,560 --> 00:24:37,040
Speaker 3: part of this narrative of trying to paint this picture

474
00:24:37,280 --> 00:24:44,119
Speaker 3: of trans folks as dangerous, as like it's somehow you know,

475
00:24:44,200 --> 00:24:46,840
Speaker 3: like it's it's because of like quote unquote mental illness.

476
00:24:46,960 --> 00:24:49,920
Speaker 3: It's these are coming from folks that already see being

477
00:24:50,040 --> 00:24:53,960
Speaker 3: trans as like a again like quote unquote mental illness,

478
00:24:54,000 --> 00:24:57,119
Speaker 3: not as like a real way of identifying and plenty

479
00:24:57,119 --> 00:24:59,920
Speaker 3: of SIS people are mentally ill, and somehow that's never

480
00:25:00,359 --> 00:25:03,440
Speaker 3: like I don't know again, it is just it's scapegoating

481
00:25:03,480 --> 00:25:06,600
Speaker 3: and is like a convenient excuse to say, like, the

482
00:25:06,680 --> 00:25:09,280
Speaker 3: problem isn't like the fact that we live in a

483
00:25:09,560 --> 00:25:12,600
Speaker 3: country that just has a deep history of violence that

484
00:25:12,680 --> 00:25:15,920
Speaker 3: like we have had, you know, problems with gun violence,

485
00:25:15,960 --> 00:25:19,640
Speaker 3: that like gun regulation is just kind of like non existent.

486
00:25:19,320 --> 00:25:19,919
Speaker 1: In this country.

487
00:25:20,000 --> 00:25:22,119
Speaker 3: It's like no, no, no, it's this specific thing that

488
00:25:22,160 --> 00:25:25,320
Speaker 3: we also don't like for other arbitrary reasons, and it's

489
00:25:25,359 --> 00:25:27,600
Speaker 3: just easy and convenient for us to tie them together

490
00:25:28,520 --> 00:25:31,240
Speaker 3: when that's not what's happening most of the time.

491
00:25:31,840 --> 00:25:34,919
Speaker 1: So this actually brings me to something that happened in

492
00:25:35,200 --> 00:25:37,639
Speaker 1: DC where I live, which was the plane crash that

493
00:25:37,720 --> 00:25:40,440
Speaker 1: happened earlier this year. There is a great piece in

494
00:25:40,520 --> 00:25:42,160
Speaker 1: Wired that will link in the show notes that folks

495
00:25:42,160 --> 00:25:45,359
Speaker 1: should read a trans pilot was falsely blamed for a

496
00:25:45,359 --> 00:25:48,520
Speaker 1: plane crash. Now she's fighting the right wing Distanto Machine

497
00:25:48,600 --> 00:25:51,199
Speaker 1: that was published earlier this summer that really unpacks this

498
00:25:51,280 --> 00:25:54,040
Speaker 1: issue in a great way. So in January there was

499
00:25:54,080 --> 00:25:57,960
Speaker 1: this deadly plane crash in DC where a helicopter crashed

500
00:25:57,960 --> 00:26:00,720
Speaker 1: into a plane. Both of them landed in the Potomac River.

501
00:26:01,040 --> 00:26:04,400
Speaker 1: Sixty seven people all died. It was a very dark

502
00:26:04,480 --> 00:26:07,600
Speaker 1: time in DC. I remember, I folks might know this

503
00:26:07,640 --> 00:26:11,120
Speaker 1: that I work part time for a DC based podcast

504
00:26:11,160 --> 00:26:15,360
Speaker 1: called Citycast DC. And DC is a pretty small community.

505
00:26:15,960 --> 00:26:20,560
Speaker 1: And so the way that this really just loomed large

506
00:26:20,640 --> 00:26:22,480
Speaker 1: at a time when d C was our when we

507
00:26:22,520 --> 00:26:24,000
Speaker 1: continue to be going through a lot, but at a

508
00:26:24,000 --> 00:26:27,439
Speaker 1: time we were going through a lot, was really rough. And

509
00:26:27,520 --> 00:26:30,600
Speaker 1: I think what made it even rougher was that. And

510
00:26:30,800 --> 00:26:33,600
Speaker 1: I promise I won't get on my DC soapbox, but

511
00:26:33,680 --> 00:26:37,919
Speaker 1: because people are so used to disrespecting DC and discounting

512
00:26:37,960 --> 00:26:39,840
Speaker 1: d C and not thinking of DC as like a

513
00:26:39,880 --> 00:26:42,720
Speaker 1: real place where real people live, it's just like a

514
00:26:42,760 --> 00:26:45,000
Speaker 1: set of national power to a lot of people. I

515
00:26:45,000 --> 00:26:47,960
Speaker 1: think the way that this was a hard tragedy for

516
00:26:48,000 --> 00:26:51,639
Speaker 1: our local DC community to take was really ignored. And

517
00:26:51,680 --> 00:26:56,520
Speaker 1: I think that's why Trump and his administration really felt okay.

518
00:26:57,280 --> 00:27:00,600
Speaker 1: Literally I mean this literally, they were bodies still in

519
00:27:00,640 --> 00:27:04,200
Speaker 1: the river while these people were lying about what happened

520
00:27:04,200 --> 00:27:06,680
Speaker 1: with this plane crash, right, And I think that one

521
00:27:06,680 --> 00:27:10,159
Speaker 1: of the reasons why that was okay is not just

522
00:27:10,200 --> 00:27:12,240
Speaker 1: because it's not just because these people are ghouls, which

523
00:27:12,280 --> 00:27:16,280
Speaker 1: they are, but also is because people in DC are

524
00:27:16,280 --> 00:27:19,920
Speaker 1: not seen as real Americans or real people the way

525
00:27:19,960 --> 00:27:22,040
Speaker 1: that other parts of the country are. So you know,

526
00:27:22,359 --> 00:27:24,760
Speaker 1: it really sucked. And as much as it was a

527
00:27:24,840 --> 00:27:28,440
Speaker 1: dark time for DC, it also became a dark time

528
00:27:28,480 --> 00:27:31,040
Speaker 1: for this woman named Joe Ellis, who is a transgender

529
00:27:31,480 --> 00:27:35,240
Speaker 1: National Guard pilot who was falsely blamed for the deadly

530
00:27:35,440 --> 00:27:39,880
Speaker 1: DC crash. Not to be super clear, Ellis was not

531
00:27:40,000 --> 00:27:44,720
Speaker 1: involved in this in any capacity, which is simply not involved. However,

532
00:27:45,280 --> 00:27:48,560
Speaker 1: a few days before this crash, Ellis published an essay

533
00:27:48,600 --> 00:27:51,000
Speaker 1: about what it's like being a trans pilot in the

534
00:27:51,080 --> 00:27:54,320
Speaker 1: National Guard. So this and this alone was enough for

535
00:27:54,480 --> 00:27:57,600
Speaker 1: right wing influencers with millions of followers across the Internet

536
00:27:57,800 --> 00:28:01,080
Speaker 1: to baselessly accuse her of being possible for this crash.

537
00:28:01,119 --> 00:28:04,679
Speaker 1: So basically what happened is that Ellis wrote this piece

538
00:28:05,119 --> 00:28:08,439
Speaker 1: called Living to Serve, Living as Myself a transgender service

539
00:28:08,480 --> 00:28:12,320
Speaker 1: members perspective, where she describes growing up in a family

540
00:28:12,520 --> 00:28:15,560
Speaker 1: of service members and then joining the Virginia Army National

541
00:28:15,600 --> 00:28:18,240
Speaker 1: Guard in two thousand and nine. In her piece, she

542
00:28:18,520 --> 00:28:21,919
Speaker 1: describes sending an email to her command giving them notice

543
00:28:21,920 --> 00:28:25,359
Speaker 1: that she intended to start transitioning under the current in

544
00:28:25,440 --> 00:28:28,959
Speaker 1: service transition policy. That policy has since been rescinded by

545
00:28:28,960 --> 00:28:31,159
Speaker 1: the Trump administration, and she talks about how when she

546
00:28:31,640 --> 00:28:34,520
Speaker 1: gave them that notice, she was met with overwhelming support

547
00:28:34,560 --> 00:28:36,919
Speaker 1: from her team. What's interesting about this piece, it's just

548
00:28:36,920 --> 00:28:39,080
Speaker 1: an interesting side note, is that it's clear that she's

549
00:28:39,080 --> 00:28:42,160
Speaker 1: trying to debunk some pretty well worn myths about how

550
00:28:42,240 --> 00:28:46,040
Speaker 1: trans people get all this free stuff, like because she

551
00:28:46,120 --> 00:28:49,480
Speaker 1: was in the military, the military is paying for all

552
00:28:49,520 --> 00:28:50,840
Speaker 1: of this stuff, and she was like, oh no, no,

553
00:28:51,040 --> 00:28:53,800
Speaker 1: I paid out of pocket for all of my care.

554
00:28:55,120 --> 00:28:57,720
Speaker 1: I paid for it all. So that even in that piece,

555
00:28:57,760 --> 00:28:59,440
Speaker 1: I feel like she's struck. You do you ever hear

556
00:28:59,480 --> 00:29:02,920
Speaker 1: this that like oh yeah.

557
00:29:02,000 --> 00:29:05,520
Speaker 3: Yeah, which I'm like, where is this free stuff?

558
00:29:05,880 --> 00:29:08,600
Speaker 1: Why am I not gonna get any of it? I mean, yeah,

559
00:29:08,640 --> 00:29:10,479
Speaker 1: any sort of trans healthcare related thing.

560
00:29:10,520 --> 00:29:12,920
Speaker 3: People hear it in there, like free healthcare, and it's

561
00:29:12,960 --> 00:29:16,360
Speaker 3: like nobody said free, Like it operates the same way

562
00:29:16,520 --> 00:29:19,920
Speaker 3: every healthcare thing in this country operates.

563
00:29:19,960 --> 00:29:23,560
Speaker 4: Which is terribly uh you know, like.

564
00:29:24,040 --> 00:29:26,719
Speaker 3: This is what really like pisses me off, especially when

565
00:29:26,760 --> 00:29:30,080
Speaker 3: we talk about again kind of a tangent issue.

566
00:29:30,120 --> 00:29:33,600
Speaker 4: But I don't know where these free handouts are.

567
00:29:33,840 --> 00:29:36,280
Speaker 3: I would if somebody knows, if somebody could get me

568
00:29:36,520 --> 00:29:38,480
Speaker 3: like some connections, please let me know.

569
00:29:39,120 --> 00:29:40,200
Speaker 1: I love free stuff.

570
00:29:40,360 --> 00:29:46,000
Speaker 3: So this is it is another example of like, unfortunately,

571
00:29:46,160 --> 00:29:48,880
Speaker 3: like the right wing just thinks that like the left

572
00:29:48,960 --> 00:29:51,840
Speaker 3: is way cooler than we actually are. Like, yeah, I

573
00:29:51,880 --> 00:29:54,400
Speaker 3: wish Joe Biden was like a communist who is just

574
00:29:54,440 --> 00:29:59,080
Speaker 3: giving people free trans healthcare, but that was absolutely not

575
00:29:59,240 --> 00:30:00,160
Speaker 3: what was happening.

576
00:30:01,080 --> 00:30:04,080
Speaker 1: And yeah, and yet here we are. What's funny about

577
00:30:04,080 --> 00:30:08,520
Speaker 1: this is that you can convince people online, especially when

578
00:30:08,560 --> 00:30:11,280
Speaker 1: it comes to gender reforming care for minors. You could

579
00:30:11,320 --> 00:30:15,160
Speaker 1: convince people like it. It's like a common sense and

580
00:30:15,240 --> 00:30:18,040
Speaker 1: just the ability to think for five seconds goes out

581
00:30:18,040 --> 00:30:21,200
Speaker 1: the window. People will say like, oh, there's doctors who

582
00:30:21,240 --> 00:30:26,040
Speaker 1: are you know, mutilating toddlers, And I swear to you

583
00:30:26,440 --> 00:30:28,600
Speaker 1: someone once told me that they have heard a story

584
00:30:28,680 --> 00:30:32,000
Speaker 1: where a doctor had given a boob job to like

585
00:30:32,040 --> 00:30:34,160
Speaker 1: a five year old, and I was thinking, like, I

586
00:30:34,160 --> 00:30:36,200
Speaker 1: cannot believe you believe this think about it for five

587
00:30:36,240 --> 00:30:37,480
Speaker 1: facus God.

588
00:30:37,560 --> 00:30:39,920
Speaker 7: That was like back when the all of the Target

589
00:30:39,960 --> 00:30:41,959
Speaker 7: stuff was happening, like this was last year I think

590
00:30:41,960 --> 00:30:45,400
Speaker 7: where there was like they were like they're selling binders

591
00:30:45,440 --> 00:30:48,280
Speaker 7: for children at Target, and it was like, look, but

592
00:30:48,400 --> 00:30:51,040
Speaker 7: like toddlers don't need binders.

593
00:30:51,120 --> 00:30:53,960
Speaker 1: You don't have boobs until you hit puberty. Like I

594
00:30:54,280 --> 00:30:56,400
Speaker 1: think about it, but it doesn't make any sense. It's

595
00:30:56,440 --> 00:30:58,480
Speaker 1: one of those I mean, it's one of those things

596
00:30:58,520 --> 00:31:01,040
Speaker 1: where if you've thought about it for five I have seconds,

597
00:31:01,560 --> 00:31:04,280
Speaker 1: it falls apart completely if if you just just thought

598
00:31:04,320 --> 00:31:06,560
Speaker 1: it through, just think get through. Sometimes I just want

599
00:31:06,560 --> 00:31:08,880
Speaker 1: to tell these people just think about it for the

600
00:31:09,240 --> 00:31:12,480
Speaker 1: most idiotic claims. But yeah, this is what I'm saying.

601
00:31:12,520 --> 00:31:16,479
Speaker 1: When it comes to moral panic around especially my like

602
00:31:16,640 --> 00:31:19,280
Speaker 1: gender reforming care for minors, you could convince them of anything.

603
00:31:19,280 --> 00:31:21,239
Speaker 1: There's like not there is not anything that is too

604
00:31:21,320 --> 00:31:23,560
Speaker 1: far gone for these people to believe, you.

605
00:31:23,520 --> 00:31:24,840
Speaker 3: Know what I d I mean, I think the thing

606
00:31:24,840 --> 00:31:26,400
Speaker 3: that I keep going back to and like thinking about

607
00:31:26,440 --> 00:31:28,320
Speaker 3: the story too, is like, at the end of the day,

608
00:31:28,520 --> 00:31:32,720
Speaker 3: none of this is coming because of like logical assumptions.

609
00:31:32,880 --> 00:31:36,120
Speaker 3: Like the hard thing is like I think it's really

610
00:31:36,120 --> 00:31:38,360
Speaker 3: easy to fall into the trap of like wanting to

611
00:31:38,840 --> 00:31:41,480
Speaker 3: like take the logical sign and be like, here, see,

612
00:31:41,560 --> 00:31:43,320
Speaker 3: you're obviously all this stuff. None of this is coming

613
00:31:43,360 --> 00:31:45,160
Speaker 3: from like a place of logic. This is coming from

614
00:31:45,240 --> 00:31:47,920
Speaker 3: the fact that like they want to find escapegoat, they

615
00:31:47,960 --> 00:31:50,800
Speaker 3: can say whatever the fuck they want and like just

616
00:31:51,400 --> 00:31:55,160
Speaker 3: speak it into being true for people's like the way

617
00:31:55,200 --> 00:31:57,080
Speaker 3: that people see the world. I think it is important

618
00:31:57,120 --> 00:31:58,960
Speaker 3: to talk about these things. It's important to emphasize the

619
00:31:58,960 --> 00:32:01,120
Speaker 3: fact that like this stuff obviously isn't true, because I

620
00:32:01,160 --> 00:32:02,320
Speaker 3: do think like at.

621
00:32:02,200 --> 00:32:04,200
Speaker 1: The end of the day, the people that are probably.

622
00:32:03,800 --> 00:32:06,640
Speaker 3: Like the most you know, the need to hear these

623
00:32:06,640 --> 00:32:09,280
Speaker 3: things are like the parents of trans kids that maybe

624
00:32:09,280 --> 00:32:12,800
Speaker 3: are like nervous about the fact that it's like, yeah, obviously,

625
00:32:12,880 --> 00:32:14,880
Speaker 3: like we live in a very transphobic world.

626
00:32:15,840 --> 00:32:17,400
Speaker 1: Your kid's gonna have to deal with that, You're gonna

627
00:32:17,440 --> 00:32:17,920
Speaker 1: have deal with that.

628
00:32:17,960 --> 00:32:20,640
Speaker 3: But it's like helping them not get sucked into these

629
00:32:20,720 --> 00:32:22,320
Speaker 3: like conspiracy.

630
00:32:21,760 --> 00:32:23,560
Speaker 1: Theory rabbit holes. But like, at the end of the day,

631
00:32:23,560 --> 00:32:24,280
Speaker 1: the people.

632
00:32:23,960 --> 00:32:26,480
Speaker 3: That are that really truly believe this stuff, that are

633
00:32:26,560 --> 00:32:29,520
Speaker 3: saying these things, like there's no way to debate them

634
00:32:29,600 --> 00:32:32,360
Speaker 3: into admitting the truth, you know, it's the whole like

635
00:32:32,560 --> 00:32:37,520
Speaker 3: Ben Shapiro brain rot thing where he's very like, oh, like,

636
00:32:37,560 --> 00:32:38,760
Speaker 3: debate me on this whatever.

637
00:32:38,880 --> 00:32:40,440
Speaker 1: Like it's like you can't debate them there.

638
00:32:40,560 --> 00:32:42,120
Speaker 4: They just they have their world view.

639
00:32:42,320 --> 00:32:45,240
Speaker 3: They know what's gonna get them the response they want,

640
00:32:45,600 --> 00:32:47,640
Speaker 3: and they're gonna say that regardless of whether it's true

641
00:32:47,720 --> 00:32:47,920
Speaker 3: or not.

642
00:32:48,520 --> 00:32:51,200
Speaker 1: Yeah, it's not like you can't debate with somebody who

643
00:32:51,280 --> 00:32:54,480
Speaker 1: is committed to misunderstanding you. There's no there's no point

644
00:32:54,560 --> 00:32:59,320
Speaker 1: in it. And so with this woman Ellis, so that's

645
00:32:59,400 --> 00:33:01,640
Speaker 1: kind of a good segway into what happened with her. So,

646
00:33:01,760 --> 00:33:05,760
Speaker 1: after her piece was published, Ellis woke up to messages

647
00:33:05,800 --> 00:33:08,320
Speaker 1: from a friend warning her that she had been named

648
00:33:08,360 --> 00:33:11,240
Speaker 1: online as the pilot who killed innocent passengers in this

649
00:33:11,320 --> 00:33:14,000
Speaker 1: deadly crash. So at first Ellis was like, oh, this

650
00:33:14,040 --> 00:33:17,320
Speaker 1: is just some sort of mistake. Somebody has mistakenly connected

651
00:33:17,320 --> 00:33:19,640
Speaker 1: me to the crash, probably because of that essay of

652
00:33:19,680 --> 00:33:22,560
Speaker 1: describing what it's like being a trans pilot from Virginia

653
00:33:22,600 --> 00:33:25,680
Speaker 1: and this accident happened near Virginia. So when she loved

654
00:33:25,680 --> 00:33:29,240
Speaker 1: into Facebook, she sees both messages from friends that are like,

655
00:33:29,280 --> 00:33:31,040
Speaker 1: oh my god, are you dead, Like I heard that

656
00:33:31,080 --> 00:33:33,760
Speaker 1: you were involved in this accident? Are you okay? And

657
00:33:34,480 --> 00:33:38,720
Speaker 1: hateful transphobic messages from people saying that they knew that

658
00:33:38,760 --> 00:33:41,320
Speaker 1: she had been involved in this crash. So here's what happened.

659
00:33:41,680 --> 00:33:44,959
Speaker 1: Right wing influencers were boosting lies that Ellis was involved

660
00:33:44,960 --> 00:33:47,720
Speaker 1: in this crash. On x Matt Wallace, who has over

661
00:33:47,760 --> 00:33:50,160
Speaker 1: two million followers, put out a post saying that a

662
00:33:50,240 --> 00:33:53,440
Speaker 1: trans black Hawk pilot had written a letter about depression

663
00:33:53,720 --> 00:33:57,040
Speaker 1: and gender dysphoria the day before the crash. He went

664
00:33:57,120 --> 00:33:59,000
Speaker 1: so far as to suggest that it was some kind

665
00:33:59,040 --> 00:34:02,240
Speaker 1: of a trans terror attack. There's that phrase again. That

666
00:34:02,320 --> 00:34:05,520
Speaker 1: post blew up got almost five million views before he

667
00:34:05,600 --> 00:34:08,600
Speaker 1: deleted it. Then Anne vander Steele, who was a pretty

668
00:34:08,600 --> 00:34:12,000
Speaker 1: well known QAnon personality with a very big following, jumped

669
00:34:12,000 --> 00:34:15,360
Speaker 1: in and pushed the same false claim. Now she eventually

670
00:34:15,360 --> 00:34:18,400
Speaker 1: posted a retraction, and it would not be an episode

671
00:34:18,480 --> 00:34:24,200
Speaker 1: about transphobia online without mentioning Elon Musk. Musk's chatbot on

672
00:34:24,680 --> 00:34:28,839
Speaker 1: xt Grock falsely named Ellis as the pilot, which only

673
00:34:29,080 --> 00:34:32,839
Speaker 1: made this rumor spread faster. So before long, Ellis's name

674
00:34:33,120 --> 00:34:35,799
Speaker 1: was trending as the second most talked about topic on

675
00:34:36,400 --> 00:34:39,120
Speaker 1: X with more than ninety thousand posts about her. She

676
00:34:39,160 --> 00:34:41,480
Speaker 1: eventually had to put out a proof of life video

677
00:34:42,080 --> 00:34:44,799
Speaker 1: on social media to reassure her community that she was

678
00:34:44,880 --> 00:34:48,160
Speaker 1: not dead and to push back against these lies. So

679
00:34:48,520 --> 00:34:52,040
Speaker 1: after she published this, Matt Wallace, one of the people

680
00:34:52,040 --> 00:34:55,000
Speaker 1: who initially pushed this claim, I will give credit where

681
00:34:55,000 --> 00:34:58,000
Speaker 1: credit is due. He did update his post to say

682
00:34:58,000 --> 00:35:01,480
Speaker 1: that Ellis was alive and not responsible for the crash.

683
00:35:01,560 --> 00:35:05,120
Speaker 1: He did also shift blame to a different account. Wala

684
00:35:05,200 --> 00:35:08,240
Speaker 1: said that the account on x called Fake Gay Politics,

685
00:35:08,239 --> 00:35:11,560
Speaker 1: which has since been suspended, was where this claim originated.

686
00:35:11,600 --> 00:35:14,280
Speaker 1: He said, this is apparently the first account who reported

687
00:35:14,320 --> 00:35:16,719
Speaker 1: what we now know is false. It seemed credible because

688
00:35:16,760 --> 00:35:19,760
Speaker 1: Joe Ellis wrote an article calling out Trump's trans military

689
00:35:19,800 --> 00:35:22,480
Speaker 1: ban only a few days ago, and of course he

690
00:35:22,520 --> 00:35:26,200
Speaker 1: goes on to misgender her in this post, saying that

691
00:35:26,280 --> 00:35:29,680
Speaker 1: he had been wrong about her causing this deadly crash

692
00:35:30,200 --> 00:35:33,000
Speaker 1: in an act of trans terror, because apparently the man

693
00:35:33,120 --> 00:35:34,200
Speaker 1: just can't help himself.

694
00:35:34,600 --> 00:35:37,319
Speaker 4: Yeah, I mean they don't. They don't care.

695
00:35:37,400 --> 00:35:38,160
Speaker 1: At the end of the day.

696
00:35:38,160 --> 00:35:40,239
Speaker 3: They don't see us as human beings, they don't see

697
00:35:40,280 --> 00:35:43,560
Speaker 3: us as legimate. So third, yeah, I am curious if

698
00:35:43,560 --> 00:35:46,920
Speaker 3: it's supposed to be this fake this account that was suspended,

699
00:35:46,960 --> 00:35:49,799
Speaker 3: if it's like fake gay politics, or if it's like

700
00:35:49,960 --> 00:35:54,520
Speaker 3: fake and gay politics, Like is it fake politics about

701
00:35:54,520 --> 00:35:56,839
Speaker 3: gay people or is it politics that is both fake

702
00:35:56,920 --> 00:35:57,399
Speaker 3: and gay?

703
00:35:58,520 --> 00:36:04,759
Speaker 1: But you know, I it's just like this is the

704
00:36:04,800 --> 00:36:05,480
Speaker 1: world we're living.

705
00:36:05,520 --> 00:36:09,359
Speaker 3: Good guy, this reminds me of I's just I can't

706
00:36:09,400 --> 00:36:09,840
Speaker 3: remember this is.

707
00:36:09,800 --> 00:36:11,759
Speaker 1: The last week or two weeks or whatever. Anyways, there

708
00:36:11,840 --> 00:36:14,240
Speaker 1: was a story we did in the News round.

709
00:36:14,200 --> 00:36:18,520
Speaker 3: Up recently about the Chris Formo getting got by an

710
00:36:18,560 --> 00:36:24,240
Speaker 3: AOC like AI video where she was like talking about

711
00:36:24,600 --> 00:36:25,840
Speaker 3: Sydney Sweeney.

712
00:36:25,520 --> 00:36:27,319
Speaker 1: Or yeah, I don't know whatever, Yeah I am.

713
00:36:27,719 --> 00:36:31,840
Speaker 3: And like his response was basically like, oh, I guess

714
00:36:32,040 --> 00:36:34,880
Speaker 3: it was a I my bad. But also it seems

715
00:36:34,920 --> 00:36:37,040
Speaker 3: like something she would say and maybe we should talk

716
00:36:37,040 --> 00:36:37,400
Speaker 3: about that.

717
00:36:37,440 --> 00:36:40,120
Speaker 1: And it's like, so you're just saying but like I

718
00:36:40,200 --> 00:36:40,879
Speaker 1: believe in my.

719
00:36:40,920 --> 00:36:43,560
Speaker 3: Fantasy world this is true, So I think we should

720
00:36:43,680 --> 00:36:45,879
Speaker 3: be we should be mad at her about like it's

721
00:36:45,880 --> 00:36:48,920
Speaker 3: like this thing where they're like but it it seems

722
00:36:49,000 --> 00:36:52,680
Speaker 3: like something that would happen, So it's an issue.

723
00:36:54,320 --> 00:36:58,040
Speaker 1: Yeah, any but it's not happening. Any random thing I

724
00:36:58,080 --> 00:37:00,239
Speaker 1: make up you need to be held accountable for Yeah,

725
00:37:00,239 --> 00:37:03,120
Speaker 1: I made exact Still in Matt Wallace's follow up tweet,

726
00:37:03,120 --> 00:37:05,040
Speaker 1: being like, well, you know, as you were saying, it

727
00:37:05,160 --> 00:37:07,839
Speaker 1: sounds like something she was talking about being depressed, and

728
00:37:07,880 --> 00:37:10,320
Speaker 1: you know, da da dada. I actually read her article

729
00:37:10,600 --> 00:37:13,920
Speaker 1: and it actually doesn't. She talks about being depressed before

730
00:37:13,960 --> 00:37:18,080
Speaker 1: she was able to transition, but in it she describes

731
00:37:18,160 --> 00:37:21,000
Speaker 1: like getting a lot of support, feeling that she has

732
00:37:21,000 --> 00:37:24,000
Speaker 1: a good support system, being really happy. Da da da da.

733
00:37:24,160 --> 00:37:25,640
Speaker 1: I think that, I mean, it goes back to what

734
00:37:25,680 --> 00:37:29,160
Speaker 1: you were saying about this default assumption that anybody who

735
00:37:29,239 --> 00:37:34,080
Speaker 1: is trans or gender non conforming is automatically mentally ill, depressed,

736
00:37:34,120 --> 00:37:38,360
Speaker 1: deeply unhappy. Because her piece is very much her describing

737
00:37:38,640 --> 00:37:42,600
Speaker 1: that she feels really good, feels really solid, wants other

738
00:37:42,680 --> 00:37:44,960
Speaker 1: people to feel as good and as solid as she does.

739
00:37:45,080 --> 00:37:48,400
Speaker 1: And still he says, oh, she's describing, you know, be

740
00:37:48,560 --> 00:37:51,239
Speaker 1: she sounds depressed. That she's like, you know, it's just

741
00:37:51,520 --> 00:37:54,160
Speaker 1: I think it really comes back to that underlying assumption

742
00:37:54,320 --> 00:37:57,120
Speaker 1: that nobody who is trans or non binary could also

743
00:37:57,200 --> 00:38:01,160
Speaker 1: be happy stable, you know, you know.

744
00:38:01,160 --> 00:38:04,319
Speaker 3: What I'm saying exactly, Yeah, I mean I think it's

745
00:38:04,360 --> 00:38:07,560
Speaker 3: interesting because I think, like even ten years ago, obviously

746
00:38:07,560 --> 00:38:10,560
Speaker 3: there are still families and places where this probably is

747
00:38:10,600 --> 00:38:13,000
Speaker 3: also the rhetoric around gay people. But I like, I'm

748
00:38:13,080 --> 00:38:14,879
Speaker 3: I'm thinking like ten years ago, I have so many

749
00:38:14,880 --> 00:38:17,359
Speaker 3: friends now that grew up with this sort of rhetoric

750
00:38:17,440 --> 00:38:19,480
Speaker 3: about gay people that were like, oh, if you're gay,

751
00:38:19,520 --> 00:38:23,919
Speaker 3: you're gonna be unhappy and depressed, versus like now was adults.

752
00:38:24,200 --> 00:38:27,040
Speaker 3: I don't know, Like again, I'm lucky where like I

753
00:38:27,120 --> 00:38:29,880
Speaker 3: live in New York City, I am in a fairly

754
00:38:30,000 --> 00:38:32,560
Speaker 3: like progressive environment.

755
00:38:32,960 --> 00:38:35,759
Speaker 4: But like, listen, I am depressed.

756
00:38:36,040 --> 00:38:38,279
Speaker 1: I have depression that has nothing to do with the

757
00:38:38,320 --> 00:38:38,759
Speaker 1: fact that I.

758
00:38:38,800 --> 00:38:41,480
Speaker 3: Am gay or trans or whatever that like, I know

759
00:38:41,600 --> 00:38:44,080
Speaker 3: plenty of sis people that are depressed. I know plenty

760
00:38:44,120 --> 00:38:47,040
Speaker 3: of most people I know these days are oppressed because

761
00:38:47,080 --> 00:38:49,640
Speaker 3: we live in a really messed up world right now.

762
00:38:51,640 --> 00:38:54,960
Speaker 1: But yeah, it is like also like yeah, shocking.

763
00:38:55,120 --> 00:38:58,560
Speaker 3: If you are living a life that is like not

764
00:38:58,680 --> 00:39:01,799
Speaker 3: authentic to yourself, if you are unable to be your

765
00:39:01,840 --> 00:39:04,000
Speaker 3: true self, you're going to feel depressed. And if you're

766
00:39:04,000 --> 00:39:06,840
Speaker 3: in a place where you're able to transition, you're able

767
00:39:06,880 --> 00:39:09,920
Speaker 3: to be the person that you really are, like on

768
00:39:09,960 --> 00:39:13,360
Speaker 3: the inside, obviously you're gonna feel better, You're gonna feel.

769
00:39:13,160 --> 00:39:14,840
Speaker 1: Happier than you were before.

770
00:39:14,880 --> 00:39:17,080
Speaker 3: And it is like, yeah, if you if you go

771
00:39:17,120 --> 00:39:19,959
Speaker 3: back and read that actual article that you wrote, That's

772
00:39:20,000 --> 00:39:21,920
Speaker 3: what she's talking about, is the fact that it's like,

773
00:39:23,160 --> 00:39:24,560
Speaker 3: at the end of the day, all of what these

774
00:39:24,600 --> 00:39:27,360
Speaker 3: people want is or trans people to just stay in

775
00:39:27,360 --> 00:39:29,319
Speaker 3: the closet and stay as theirs signed gender at birth.

776
00:39:29,360 --> 00:39:31,720
Speaker 1: And it's like, great, that is you're.

777
00:39:31,600 --> 00:39:36,880
Speaker 3: Creating these like depressed just like like the things that

778
00:39:36,920 --> 00:39:39,040
Speaker 3: you think are going to happen if people transition, that's

779
00:39:39,080 --> 00:39:41,080
Speaker 3: just what's going to happen. If you continue to stay repressed,

780
00:39:41,080 --> 00:39:43,919
Speaker 3: you're gonna you're gonna not you know, the terrorism part,

781
00:39:43,960 --> 00:39:46,320
Speaker 3: but like the people are gonna be depressed and miserable,

782
00:39:46,480 --> 00:39:49,080
Speaker 3: and like that is what leads to suicide in a

783
00:39:49,080 --> 00:39:52,080
Speaker 3: lot of cases. Uh, not the fact that people are

784
00:39:52,080 --> 00:39:56,239
Speaker 3: trans the fact that people are not allowed to express

785
00:39:56,360 --> 00:39:59,680
Speaker 3: themselves and to be like the person that they.

786
00:39:59,600 --> 00:40:05,120
Speaker 1: Are, you know exactly. It is oppressive systems and lack

787
00:40:05,200 --> 00:40:08,720
Speaker 1: of access to meaningful support systems that makes people unhappy

788
00:40:08,719 --> 00:40:10,600
Speaker 1: and it makes people unwell. And this idea that like

789
00:40:10,640 --> 00:40:13,760
Speaker 1: oh well and again, but trans people and queer people

790
00:40:13,920 --> 00:40:17,320
Speaker 1: should not have to I mean, yeah, let trans people

791
00:40:17,320 --> 00:40:20,200
Speaker 1: be depressed and said like they should not have to

792
00:40:20,239 --> 00:40:22,600
Speaker 1: be like, oh, I'm super good. I'm super good, because

793
00:40:22,600 --> 00:40:24,640
Speaker 1: nobody is super good all the time. But what creates

794
00:40:24,719 --> 00:40:28,960
Speaker 1: dynamics where it's not it's not transness or queerness that

795
00:40:29,080 --> 00:40:33,800
Speaker 1: makes people depressed, it is lack of access, lack of resources,

796
00:40:33,880 --> 00:40:36,840
Speaker 1: lack of support. Like, we've created a system that allows

797
00:40:36,920 --> 00:40:40,000
Speaker 1: us to blame people for the things that our system

798
00:40:40,080 --> 00:40:44,000
Speaker 1: denies them.

799
00:40:44,000 --> 00:40:56,640
Speaker 5: More after a quick break, let's.

800
00:40:56,400 --> 00:40:59,920
Speaker 1: Get right back into it. So we're talking about Joel,

801
00:41:00,400 --> 00:41:03,880
Speaker 1: this trans pilot who extremists on the internet falsely accused

802
00:41:03,920 --> 00:41:06,480
Speaker 1: of being responsible for the deadly plane crash in DC

803
00:41:06,600 --> 00:41:09,960
Speaker 1: earlier this year. Figures like Matt Wallace accused her of

804
00:41:10,000 --> 00:41:14,040
Speaker 1: waging eight trans terror attack, even though she had absolutely

805
00:41:14,080 --> 00:41:18,080
Speaker 1: nothing to do with this crash. So, from this point,

806
00:41:18,120 --> 00:41:21,160
Speaker 1: Ellis basically went from being unknown in public to being

807
00:41:21,160 --> 00:41:23,160
Speaker 1: somebody who felt like she could not even go out

808
00:41:23,200 --> 00:41:26,080
Speaker 1: in public because for fear of her own safety. She

809
00:41:26,160 --> 00:41:28,520
Speaker 1: told The New York Times, my life was turned upside

810
00:41:28,560 --> 00:41:31,320
Speaker 1: down at that point, adding that her employers sent armed

811
00:41:31,360 --> 00:41:33,880
Speaker 1: bodyguards to protect her family and that she started carrying

812
00:41:33,880 --> 00:41:36,920
Speaker 1: a loaded weapon as a precaution. Forever I'm known as

813
00:41:37,040 --> 00:41:40,719
Speaker 1: that trans terrorist, she told The Times. So we've talked

814
00:41:40,719 --> 00:41:43,560
Speaker 1: about this in a few other episodes of the podcast.

815
00:41:43,640 --> 00:41:48,960
Speaker 1: But when online right wing influencers, individual influencers spread lies

816
00:41:49,000 --> 00:41:52,000
Speaker 1: about people, we're seeing more and more that the people

817
00:41:52,040 --> 00:41:57,120
Speaker 1: that they defame are fighting back via defamation lawsuits targeted

818
00:41:57,160 --> 00:42:00,719
Speaker 1: at the people who spread demonstrably and hurtful lies about them.

819
00:42:00,719 --> 00:42:03,200
Speaker 1: And so that's exactly what Ellis did. In April, she

820
00:42:03,280 --> 00:42:05,719
Speaker 1: filed a defamation suit against Matt Wallace, saying that he

821
00:42:05,800 --> 00:42:10,520
Speaker 1: was behind a destructive and irresponsible defamation campaign. The lawsuit

822
00:42:10,520 --> 00:42:13,200
Speaker 1: against Wallace, filed in the U. S. District Court of Colorado,

823
00:42:13,400 --> 00:42:15,120
Speaker 1: was a way for Elis to seek damages for the

824
00:42:15,160 --> 00:42:19,240
Speaker 1: harm that he caused her reputation, privacy, and safety. Ellis

825
00:42:19,239 --> 00:42:22,040
Speaker 1: said that Wallace has not counterfiled, and the lawsuit was

826
00:42:22,080 --> 00:42:24,040
Speaker 1: filed by the Equality Legal Action Fund, which is a

827
00:42:24,040 --> 00:42:26,520
Speaker 1: group of volunteer attorneys and advocates who helped members of

828
00:42:26,520 --> 00:42:30,799
Speaker 1: the LGBTQ community fight online defamation. It does sound to

829
00:42:30,840 --> 00:42:33,040
Speaker 1: me like when I looked into this, that it might

830
00:42:33,080 --> 00:42:35,520
Speaker 1: be a little bit of a tricky gray area legally

831
00:42:35,640 --> 00:42:40,399
Speaker 1: to individually sue an individual online influencer for what they've

832
00:42:40,400 --> 00:42:43,319
Speaker 1: said about you. Parents of kids who died in the

833
00:42:43,360 --> 00:42:47,480
Speaker 1: Sandy Hook shooting did successfully sue Alex Jones for defamation

834
00:42:47,600 --> 00:42:50,080
Speaker 1: after he repeatedly claimed that the shooting that killed their

835
00:42:50,160 --> 00:42:53,279
Speaker 1: kids was basically a hoax. And folks might remember that

836
00:42:53,280 --> 00:42:56,000
Speaker 1: Dominion Voting Systems got a seven hundred and eighty seven

837
00:42:56,040 --> 00:42:59,279
Speaker 1: million dollar settlement from Fox News for claiming that their

838
00:42:59,360 --> 00:43:02,279
Speaker 1: voting systems during the election we're rigged against Trump. So

839
00:43:02,360 --> 00:43:07,200
Speaker 1: there is some precedent for suing businesses or business entities

840
00:43:07,480 --> 00:43:10,160
Speaker 1: for defamation, but that's a little bit different than these

841
00:43:10,280 --> 00:43:15,200
Speaker 1: one off individual influencers on Twitter who spread damaging lies

842
00:43:15,239 --> 00:43:19,280
Speaker 1: about people. And you know, I hate that the only

843
00:43:19,440 --> 00:43:22,600
Speaker 1: recourse for this kind of thing is suing people and

844
00:43:23,360 --> 00:43:26,440
Speaker 1: taking it to the courts. But especially for marginalized people,

845
00:43:26,640 --> 00:43:28,600
Speaker 1: there has to be some kind of accountability for this.

846
00:43:28,640 --> 00:43:30,520
Speaker 1: There has to be some sort of like cost for

847
00:43:30,640 --> 00:43:33,520
Speaker 1: spreading these kinds of damaging lies, because these kind of

848
00:43:33,600 --> 00:43:36,440
Speaker 1: lies can hurt people. You know, we've talked about Ruby

849
00:43:36,440 --> 00:43:40,000
Speaker 1: Freeman and Shay Moss, the two black women in Georgia

850
00:43:40,000 --> 00:43:43,959
Speaker 1: who were vote counters who Trump and Giuliani baselessly said

851
00:43:44,000 --> 00:43:46,200
Speaker 1: that they had rigged the elect They were hiding votes

852
00:43:46,239 --> 00:43:50,160
Speaker 1: and rigging the election for Biden. People showed up at

853
00:43:50,239 --> 00:43:53,080
Speaker 1: their house and tried to force their way into their

854
00:43:53,120 --> 00:43:55,920
Speaker 1: home to make a citizens arrest because of that. So, like,

855
00:43:56,320 --> 00:44:00,680
Speaker 1: this is not something that happens online. This translates to actual,

856
00:44:00,880 --> 00:44:03,720
Speaker 1: real world to harm where people are putting their lives

857
00:44:03,719 --> 00:44:06,320
Speaker 1: at risk because of the lies people spread about them online.

858
00:44:07,480 --> 00:44:08,680
Speaker 4: Yeah, totally agree.

859
00:44:08,760 --> 00:44:13,560
Speaker 3: I mean, it's I wish there was another like, I

860
00:44:13,560 --> 00:44:16,319
Speaker 3: wish there was something that could happen before having to

861
00:44:16,600 --> 00:44:20,800
Speaker 3: like literally sue these people. But good for Joe Alice.

862
00:44:20,960 --> 00:44:24,880
Speaker 3: I hope that that case goes in you know, her favor.

863
00:44:25,719 --> 00:44:29,840
Speaker 3: But yeah, it really I think it's important to emphasize

864
00:44:29,840 --> 00:44:32,439
Speaker 3: the fact that it's like this isn't just like, oh,

865
00:44:32,560 --> 00:44:36,799
Speaker 3: I'm getting a bunch of hate comments online, you can

866
00:44:36,840 --> 00:44:39,520
Speaker 3: just turn your phone off and not pay attention to it.

867
00:44:39,520 --> 00:44:43,480
Speaker 3: It's like this is affecting people's like actual livelihood. It

868
00:44:43,560 --> 00:44:48,520
Speaker 3: is affecting their ability to exist in public, and that

869
00:44:48,760 --> 00:44:52,600
Speaker 3: should not be happening because that shouldn't be happening to anyone.

870
00:44:52,719 --> 00:44:55,440
Speaker 3: But it's hard enough to exist as a trans person,

871
00:44:55,640 --> 00:44:57,480
Speaker 3: as like a person of color, as a queer person,

872
00:44:57,640 --> 00:45:01,680
Speaker 3: anybody with any sort of marginalized right now, Like, there

873
00:45:01,719 --> 00:45:06,480
Speaker 3: shouldn't be an extra layer of being this level of

874
00:45:06,520 --> 00:45:07,200
Speaker 3: like a target.

875
00:45:07,760 --> 00:45:11,799
Speaker 1: And I hate that this is such a commonplace thing now,

876
00:45:11,800 --> 00:45:14,279
Speaker 1: because blaming trans folks for incidents that they literally had

877
00:45:14,320 --> 00:45:17,799
Speaker 1: nothing to do with is not an isolated thing. The

878
00:45:17,800 --> 00:45:20,520
Speaker 1: fact Checking Database Claim Review shows that since twenty twenty two,

879
00:45:20,560 --> 00:45:23,280
Speaker 1: there have been a dozen incidents where a transgender person

880
00:45:23,360 --> 00:45:26,520
Speaker 1: was wrongly blamed for a tragedy or violent incident. After

881
00:45:26,600 --> 00:45:29,640
Speaker 1: the tragic deaths of Minnesota state a representative Mussa Hortman

882
00:45:29,680 --> 00:45:33,880
Speaker 1: and her husband who were assassinated, Donald Trump Junior said, quote,

883
00:45:33,960 --> 00:45:37,240
Speaker 1: the radical transgender movement is, per capita, the most violent

884
00:45:37,239 --> 00:45:40,760
Speaker 1: domestic terror threat in America, if not probably the entire world.

885
00:45:40,960 --> 00:45:43,040
Speaker 1: And that shooter was not even trans.

886
00:45:43,880 --> 00:45:46,040
Speaker 3: I think that was the quote I was thinking about earlier,

887
00:45:46,120 --> 00:45:47,480
Speaker 3: Like I was like, I know there was something where

888
00:45:47,560 --> 00:45:51,120
Speaker 3: somebody was like the most violent domestic terror threat. I

889
00:45:51,200 --> 00:45:56,880
Speaker 3: was like, well, really, I am sure about that. Yeah, No,

890
00:45:57,080 --> 00:45:57,680
Speaker 3: that's crazy.

891
00:45:57,760 --> 00:46:01,440
Speaker 1: That literally was like a right wing attack. Yeah, that

892
00:46:01,560 --> 00:46:05,640
Speaker 1: happened very explicitly and clearly and after two people were

893
00:46:05,719 --> 00:46:09,360
Speaker 1: killed in Wisconsin, Alex Jones, who really should not be

894
00:46:09,600 --> 00:46:13,960
Speaker 1: lying about anybody, publicly tweeted if the statistical trend continues

895
00:46:14,000 --> 00:46:16,239
Speaker 1: with this tragic event, there's a ninety eight percent chance

896
00:46:16,280 --> 00:46:19,600
Speaker 1: the shooting is trans or gang related. If it's another

897
00:46:19,680 --> 00:46:22,279
Speaker 1: trans whack job or gang shooting, it should be out

898
00:46:22,280 --> 00:46:24,560
Speaker 1: of the news in less than twenty four hours. So

899
00:46:25,040 --> 00:46:27,360
Speaker 1: it che go without saying that this is all a

900
00:46:27,400 --> 00:46:31,279
Speaker 1: complete lie. Trans people are more likely to be the

901
00:46:31,400 --> 00:46:34,440
Speaker 1: victims of crime, not the perpetrators. This is from Wired

902
00:46:35,000 --> 00:46:37,759
Speaker 1: research those that trans people are four times more likely

903
00:46:37,800 --> 00:46:39,840
Speaker 1: to be the victims of violence compared to cist people.

904
00:46:40,160 --> 00:46:43,000
Speaker 1: According to GLAD, between May twenty twenty four and May

905
00:46:43,000 --> 00:46:45,200
Speaker 1: twenty twenty five, there have been at least twenty six

906
00:46:45,239 --> 00:46:48,160
Speaker 1: injuries and one death reported among trans and non and

907
00:46:48,200 --> 00:46:51,120
Speaker 1: gender non conforming people, a fourteen percent jump from the

908
00:46:51,160 --> 00:46:54,879
Speaker 1: previous year. Meanwhile, claims that trans folks are behind mass

909
00:46:54,920 --> 00:46:58,320
Speaker 1: shootings just does not add up. Per the Gun Violence Archive,

910
00:46:58,360 --> 00:47:01,440
Speaker 1: there have been four four hundred shootings in the past decade,

911
00:47:01,920 --> 00:47:05,399
Speaker 1: of which fewer than ten known suspects were trans. That's

912
00:47:05,440 --> 00:47:08,360
Speaker 1: zero point eleven percent, and we know that things like

913
00:47:08,440 --> 00:47:12,279
Speaker 1: far right extremism surpasses terrorism committed by others. This is

914
00:47:12,280 --> 00:47:14,319
Speaker 1: according to politifacts, and it needs to be said that

915
00:47:14,400 --> 00:47:17,080
Speaker 1: these groups do tend to engage in violence that often

916
00:47:17,200 --> 00:47:23,480
Speaker 1: targets LGBTQ people and promotes LGBTQ views. So making the

917
00:47:23,719 --> 00:47:26,600
Speaker 1: targets the people who are the most targeted of this

918
00:47:26,719 --> 00:47:29,600
Speaker 1: kind of domestic terror, flipping that around and being like, oh,

919
00:47:29,640 --> 00:47:33,360
Speaker 1: they all they're the perpetrators. It's really blaming people for

920
00:47:33,600 --> 00:47:35,600
Speaker 1: something bad that they are already at the center of.

921
00:47:36,280 --> 00:47:41,399
Speaker 3: Yeah, people actually don't know this, but uh the Lee

922
00:47:41,480 --> 00:47:46,759
Speaker 3: Harvey Oswald actually used gi the pronouns they governed this

923
00:47:47,040 --> 00:47:49,160
Speaker 3: lister kidding.

924
00:47:49,080 --> 00:47:50,960
Speaker 1: I'm not even honestly, I feel like.

925
00:47:50,960 --> 00:47:53,960
Speaker 3: We're like two steps away from somebody transvestigating.

926
00:47:54,120 --> 00:47:57,640
Speaker 1: Yeah, like yeah, like a deep dive. But this exactly

927
00:47:57,800 --> 00:48:02,000
Speaker 1: exactly like why you're RESI. I mean, Glad has a

928
00:48:02,000 --> 00:48:04,600
Speaker 1: lot of really great studies, you.

929
00:48:04,560 --> 00:48:09,279
Speaker 3: Know, shameless plug for a second if you want to

930
00:48:09,360 --> 00:48:12,319
Speaker 3: learn more about violence against the transcunities. So we should

931
00:48:12,360 --> 00:48:14,560
Speaker 3: check out another show that I work on that's called Afterlives.

932
00:48:15,080 --> 00:48:18,240
Speaker 3: Our first season was about this woman Leiley and Planco

933
00:48:18,400 --> 00:48:22,400
Speaker 3: who passed away at Briker's prison due to kind of

934
00:48:22,480 --> 00:48:26,280
Speaker 3: a series of just things that should not have happened,

935
00:48:26,360 --> 00:48:29,560
Speaker 3: situations she not had been in, largely because of the

936
00:48:29,560 --> 00:48:32,320
Speaker 3: fact that she was a black trans woman. But something

937
00:48:32,320 --> 00:48:34,000
Speaker 3: that we talked about in that show that we did

938
00:48:34,040 --> 00:48:37,319
Speaker 3: a lot of research around was this idea that when

939
00:48:37,360 --> 00:48:40,840
Speaker 3: you look at the way that trans people, the few

940
00:48:41,000 --> 00:48:45,520
Speaker 3: instances of trans people being portrayed in like TV and film,

941
00:48:45,920 --> 00:48:49,720
Speaker 3: even before trans people became the scapegoat for mass shootings

942
00:48:49,760 --> 00:48:52,400
Speaker 3: and this kind of thing, the way that trans people

943
00:48:52,480 --> 00:48:56,719
Speaker 3: were portrayed as like murderers and criminal, like looking back

944
00:48:56,719 --> 00:48:59,120
Speaker 3: at like Silence of the Lambs and stuff like that,

945
00:48:59,160 --> 00:49:02,720
Speaker 3: where there's like this whole history of trans folks being

946
00:49:02,760 --> 00:49:07,839
Speaker 3: portrayed as violent, being portrayed as like unstable, when it's like,

947
00:49:08,400 --> 00:49:12,879
Speaker 3: at the same time, we are disproportionally, and particularly trans

948
00:49:12,920 --> 00:49:17,719
Speaker 3: women and particularly transmomant of color, are disproportionally the victims

949
00:49:17,760 --> 00:49:20,040
Speaker 3: of this kind of violence, and it is sort of

950
00:49:20,080 --> 00:49:23,600
Speaker 3: like again pulling back, it is frustrating to have to

951
00:49:23,719 --> 00:49:26,719
Speaker 3: keep having this conversation and have to keep being like, no,

952
00:49:26,840 --> 00:49:29,719
Speaker 3: we are not the ones that are doing this, when

953
00:49:29,760 --> 00:49:32,040
Speaker 3: it's like, also at the same time, our community is

954
00:49:32,120 --> 00:49:35,840
Speaker 3: being targeted in this way, we're like people are dying,

955
00:49:35,920 --> 00:49:40,359
Speaker 3: people are like being murdered, people are like anti transa crime,

956
00:49:40,480 --> 00:49:43,800
Speaker 3: Like those anti transa crimes are happening.

957
00:49:43,840 --> 00:49:45,640
Speaker 4: People are dying because they're trans.

958
00:49:45,960 --> 00:49:49,520
Speaker 3: And at the same time, like the way that trans

959
00:49:49,600 --> 00:49:53,520
Speaker 3: people are oftentimes like portrayed by these like right wing groups,

960
00:49:53,520 --> 00:49:56,520
Speaker 3: but also in a lot of like mainstream entertainment, it's

961
00:49:57,400 --> 00:49:59,520
Speaker 3: makes it appear as if we're the ones that are

962
00:49:59,520 --> 00:49:59,799
Speaker 3: doing this.

963
00:50:00,920 --> 00:50:04,480
Speaker 1: It's so true, and I wish so I could say

964
00:50:04,480 --> 00:50:06,400
Speaker 1: that we have moved that we have because like you

965
00:50:06,440 --> 00:50:09,360
Speaker 1: go back and watch movies like Pet Detective and not

966
00:50:09,360 --> 00:50:11,239
Speaker 1: not to like spoil the movie.

967
00:50:11,000 --> 00:50:13,880
Speaker 3: But I okay, that what's funny because I've never actually

968
00:50:13,920 --> 00:50:17,240
Speaker 3: seen that movie, but I feel like every like trans

969
00:50:17,320 --> 00:50:20,400
Speaker 3: mask person at some point is like I look like

970
00:50:20,520 --> 00:50:22,759
Speaker 3: a svener Pet And it's like at the same time,

971
00:50:22,800 --> 00:50:26,359
Speaker 3: that movie is so transforthing, and it's funny we have.

972
00:50:26,320 --> 00:50:28,320
Speaker 1: Not like we It's I wish I could say that

973
00:50:28,360 --> 00:50:31,800
Speaker 1: we had beyond that that like portrayal from like nineteen

974
00:50:31,840 --> 00:50:34,279
Speaker 1: ninety two or whatever. But you're right, we really have

975
00:50:34,320 --> 00:50:35,840
Speaker 1: it when you look at the way that and I

976
00:50:36,120 --> 00:50:39,200
Speaker 1: guess it's why it's so important that work like your

977
00:50:39,320 --> 00:50:42,560
Speaker 1: work with Afterlives, you know, it's very important that we

978
00:50:42,680 --> 00:50:46,760
Speaker 1: have depictions of trans folks in ways that are thoughtful

979
00:50:46,840 --> 00:50:50,520
Speaker 1: and loving and real and aren't out of like, yeah,

980
00:50:50,560 --> 00:50:52,360
Speaker 1: we we need the work that you all are doing.

981
00:50:53,600 --> 00:50:54,000
Speaker 1: Thank you.

982
00:50:54,320 --> 00:50:56,160
Speaker 4: Yeah, I got shapeless plug.

983
00:50:56,239 --> 00:50:59,959
Speaker 3: Go listen to Afterlives works very hard on that show,

984
00:51:00,200 --> 00:51:06,680
Speaker 3: but on the tangent just about friends, people and how

985
00:51:06,719 --> 00:51:10,359
Speaker 3: we're portrayed, both like in news media and entertainment media.

986
00:51:10,400 --> 00:51:12,719
Speaker 3: I think there was there was an interview with Jenks

987
00:51:12,760 --> 00:51:14,840
Speaker 3: Bond soon recently where she was talking about like she

988
00:51:15,080 --> 00:51:17,440
Speaker 3: like playing she played like a villain and like doctor

989
00:51:17,520 --> 00:51:22,160
Speaker 3: Who recently, and she was talking about like being as

990
00:51:22,160 --> 00:51:26,000
Speaker 3: an actress, like getting to play roles where she is

991
00:51:26,000 --> 00:51:28,600
Speaker 3: like a villain as a transperson, and how like it's

992
00:51:28,600 --> 00:51:30,600
Speaker 3: almost kind of liberating because it's like she's able to

993
00:51:30,480 --> 00:51:33,400
Speaker 3: do like kind of reain control.

994
00:51:33,280 --> 00:51:34,080
Speaker 1: Of that narrative.

995
00:51:34,120 --> 00:51:35,440
Speaker 3: Like it was sort of she was talking about the

996
00:51:35,480 --> 00:51:36,840
Speaker 3: fact that it's like we're all like Villa and I

997
00:51:37,040 --> 00:51:38,640
Speaker 3: so much all of this stuff is put on us,

998
00:51:38,680 --> 00:51:40,120
Speaker 3: and it's like almost kind of fun to be able

999
00:51:40,160 --> 00:51:42,640
Speaker 3: to like twist that around and get to play, you know,

1000
00:51:42,800 --> 00:51:46,000
Speaker 3: into like being like an in evil character that has

1001
00:51:46,080 --> 00:51:49,200
Speaker 3: nothing to do with being friends anyways, tangent has nothing

1002
00:51:49,320 --> 00:51:51,759
Speaker 3: really to do with this, But yeah, I think there

1003
00:51:51,840 --> 00:51:53,439
Speaker 3: is something to be said about the fact that it's

1004
00:51:53,480 --> 00:51:56,360
Speaker 3: like the stuff that we consume shapes the way that

1005
00:51:56,360 --> 00:51:59,440
Speaker 3: we think about people. And that means you know, that

1006
00:51:59,520 --> 00:52:02,360
Speaker 3: means dude, media, that means entertainment, media that means these,

1007
00:52:02,480 --> 00:52:05,760
Speaker 3: that means Twitter, you know, yeah, in social media, and.

1008
00:52:05,640 --> 00:52:12,160
Speaker 1: That is why these sort of things are dangerous. More

1009
00:52:12,200 --> 00:52:24,839
Speaker 1: after a quick break, let's get right back into it.

1010
00:52:26,719 --> 00:52:29,200
Speaker 1: We really can't talk about the mechanics of how trans

1011
00:52:29,239 --> 00:52:32,920
Speaker 1: people get falsely linked to violence without talking about the

1012
00:52:33,040 --> 00:52:36,439
Speaker 1: media apparatus that facilitates it. One of the biggest parts

1013
00:52:36,480 --> 00:52:38,920
Speaker 1: of this story is that the way that they have

1014
00:52:39,040 --> 00:52:42,120
Speaker 1: really built an effective media apparatus where these claims might

1015
00:52:42,239 --> 00:52:44,640
Speaker 1: start in more fringe pockets of the Internet, like for

1016
00:52:44,800 --> 00:52:48,399
Speaker 1: Chune or some random extremist Twitter page, but they then

1017
00:52:48,480 --> 00:52:52,000
Speaker 1: pretty quickly get boosted by right wing politicians, media figures,

1018
00:52:52,160 --> 00:52:55,440
Speaker 1: and even bleed into mainstream media where they just become

1019
00:52:55,560 --> 00:52:57,960
Speaker 1: part of people's conscious like they just like become as

1020
00:52:58,000 --> 00:53:00,960
Speaker 1: part of how people understand trans folks. And then it's

1021
00:53:01,000 --> 00:53:04,360
Speaker 1: all made worse by the fact that social media platforms

1022
00:53:04,360 --> 00:53:08,200
Speaker 1: have really mostly all of them, loosened whatever rules they

1023
00:53:08,280 --> 00:53:11,920
Speaker 1: did have to prevent people from really being ugly and

1024
00:53:12,000 --> 00:53:15,200
Speaker 1: horrible to trans and queer people. Right Like, earlier this year,

1025
00:53:15,320 --> 00:53:18,880
Speaker 1: Facebook loosened rules around hate speech and abuse. LinkedIn recently

1026
00:53:19,120 --> 00:53:22,359
Speaker 1: changed their policies. It's a little bit of a complicated thing,

1027
00:53:22,400 --> 00:53:25,400
Speaker 1: but it does seem that they are making it easier

1028
00:53:25,400 --> 00:53:28,000
Speaker 1: for folks to miss gender and dead name people on LinkedIn,

1029
00:53:28,080 --> 00:53:31,400
Speaker 1: of all places. No, yeah, that's like what I was like,

1030
00:53:31,440 --> 00:53:32,120
Speaker 1: are you kidding me?

1031
00:53:32,320 --> 00:53:32,960
Speaker 4: Like LinkedIn?

1032
00:53:33,560 --> 00:53:36,760
Speaker 3: Like what it's not first of all, the people use LinkedIn,

1033
00:53:36,840 --> 00:53:41,160
Speaker 3: like it's an actual social media platform. Like that's to me,

1034
00:53:41,600 --> 00:53:43,560
Speaker 3: those are the people we should be concerned about.

1035
00:53:43,680 --> 00:53:50,799
Speaker 1: Like that's something's going on. But like, I don't know.

1036
00:53:50,960 --> 00:53:54,680
Speaker 3: I was like, I check LinkedIn when I absolutely have to.

1037
00:53:54,880 --> 00:53:58,400
Speaker 3: Like I was like, this is literally just how I

1038
00:53:58,560 --> 00:54:00,759
Speaker 3: show what my job is. I don't like, this has

1039
00:54:00,800 --> 00:54:04,600
Speaker 3: nothing to do. But I don't know, Come on, LinkedIn,

1040
00:54:04,760 --> 00:54:05,160
Speaker 3: I get you.

1041
00:54:05,239 --> 00:54:09,680
Speaker 1: A whole better. It's like, yeah, I don't I would do.

1042
00:54:09,719 --> 00:54:11,880
Speaker 1: I could talk to you. I have a lot to

1043
00:54:11,920 --> 00:54:16,279
Speaker 1: say about LinkedIn. I'm a LinkedIn hater, I will. You know,

1044
00:54:18,239 --> 00:54:20,840
Speaker 1: so all of this becomes a bigger problem when you

1045
00:54:20,880 --> 00:54:25,320
Speaker 1: look at how algorithms amplify harmful content, and platforms like

1046
00:54:25,400 --> 00:54:28,600
Speaker 1: Facebook and x have really just scrapped fact checking. There's

1047
00:54:28,640 --> 00:54:32,319
Speaker 1: not really meaningful bactchecking happening on these platforms anymore where

1048
00:54:32,320 --> 00:54:35,160
Speaker 1: people could push back and say, hey, this person is

1049
00:54:35,160 --> 00:54:38,759
Speaker 1: not a trans terror suspect or whatever. And like I

1050
00:54:38,840 --> 00:54:42,120
Speaker 1: was saying, you know, all of this just becomes another

1051
00:54:42,280 --> 00:54:46,839
Speaker 1: system that dehumanizes trans people, justifies violence against trans people

1052
00:54:46,880 --> 00:54:49,120
Speaker 1: who are already targets of violence, as we talked about,

1053
00:54:49,360 --> 00:54:53,239
Speaker 1: you know, continues to to dehumanize trans people, and I

1054
00:54:53,239 --> 00:54:55,760
Speaker 1: think it kind of goes to what we were saying earlier.

1055
00:54:55,840 --> 00:54:58,759
Speaker 1: Like to me, the whole thing really shows just how

1056
00:54:58,840 --> 00:55:01,719
Speaker 1: eager people are to use anything, even if it is

1057
00:55:01,760 --> 00:55:06,200
Speaker 1: outright lies, to paint trans people as mentally ill or violent.

1058
00:55:06,280 --> 00:55:08,280
Speaker 1: And it is like it's like they're trying to build

1059
00:55:08,280 --> 00:55:11,280
Speaker 1: a world where trans people never just get to exist

1060
00:55:11,440 --> 00:55:14,520
Speaker 1: as their selves, whether that is someone who is depressed

1061
00:55:14,640 --> 00:55:18,240
Speaker 1: or said or happy or a meaty villain or whatever,

1062
00:55:18,360 --> 00:55:21,600
Speaker 1: Like you never get to just be who you are. Instead,

1063
00:55:21,600 --> 00:55:25,080
Speaker 1: they're being like constantly held responsible for not just what

1064
00:55:25,120 --> 00:55:28,480
Speaker 1: other trans people do, but for things that never even

1065
00:55:28,560 --> 00:55:30,480
Speaker 1: actually happened in the first place.

1066
00:55:31,040 --> 00:55:32,799
Speaker 3: This kind of reminds me. I was talking with a

1067
00:55:32,800 --> 00:55:36,040
Speaker 3: friend recently about like, because again, like I'm lucky enough

1068
00:55:36,040 --> 00:55:40,360
Speaker 3: for like I have a pretty solid like trans community

1069
00:55:40,360 --> 00:55:42,600
Speaker 3: where I am, and like queer community, and I was

1070
00:55:42,600 --> 00:55:45,040
Speaker 3: talking with a friend recently about how we're like it's

1071
00:55:45,040 --> 00:55:49,320
Speaker 3: always annoying while like we have like stupid, like interpersonal

1072
00:55:50,040 --> 00:55:53,719
Speaker 3: beef with people that also just happen to be like

1073
00:55:53,800 --> 00:55:57,000
Speaker 3: trans or queer or whatever, and being like, yeah, like

1074
00:55:57,120 --> 00:55:57,680
Speaker 3: they suck.

1075
00:55:57,760 --> 00:55:58,840
Speaker 1: They did all of this stuff.

1076
00:55:58,880 --> 00:56:00,840
Speaker 3: I don't like them, but all so like at the

1077
00:56:00,960 --> 00:56:04,240
Speaker 3: end of the day, we're all being attacked right now,

1078
00:56:04,280 --> 00:56:07,319
Speaker 3: so like I hope that they you know, like I

1079
00:56:07,320 --> 00:56:09,239
Speaker 3: don't want them to get hate crimed.

1080
00:56:09,360 --> 00:56:12,719
Speaker 4: I don't want them to get like I hope that.

1081
00:56:12,719 --> 00:56:14,720
Speaker 1: None of this awful stuff happens.

1082
00:56:14,880 --> 00:56:16,680
Speaker 3: Like it's like, oh great, I have to defend the

1083
00:56:16,760 --> 00:56:20,759
Speaker 3: worst person I know because we're all being attacked right now,

1084
00:56:20,800 --> 00:56:22,239
Speaker 3: and it's like I should be able to just be

1085
00:56:22,280 --> 00:56:23,240
Speaker 3: a hater in peace.

1086
00:56:24,480 --> 00:56:25,799
Speaker 1: That is the biggest crime here.

1087
00:56:26,800 --> 00:56:31,080
Speaker 3: But no, but yeah, it really is like trains people

1088
00:56:31,080 --> 00:56:34,000
Speaker 3: are such a like small portion of the population. Even

1089
00:56:34,000 --> 00:56:37,200
Speaker 3: if we weren't, who cares, Like, even if we weren't,

1090
00:56:37,200 --> 00:56:39,359
Speaker 3: because that's something people always like emphasize. It's like, oh,

1091
00:56:39,360 --> 00:56:43,719
Speaker 3: it's such a small percentage of the population. But it's like, yeah,

1092
00:56:43,760 --> 00:56:47,920
Speaker 3: we're just people. Like it doesn't affect how like how

1093
00:56:48,000 --> 00:56:50,680
Speaker 3: someone else is presenting, how somebody else is identifying, how

1094
00:56:50,680 --> 00:56:52,560
Speaker 3: they're living their life has nothing to do with you.

1095
00:56:52,760 --> 00:56:56,279
Speaker 4: And like we're at this point with politics where it's

1096
00:56:56,320 --> 00:56:57,080
Speaker 4: like this.

1097
00:56:56,960 --> 00:56:59,640
Speaker 3: Has like so much of the noise is just this

1098
00:56:59,760 --> 00:57:02,640
Speaker 3: kind of stuff because it takes away from like the

1099
00:57:02,800 --> 00:57:05,920
Speaker 3: actual issues in it. And again, like people have died,

1100
00:57:06,160 --> 00:57:08,399
Speaker 3: Like there are two children that are dead right now.

1101
00:57:08,800 --> 00:57:12,000
Speaker 3: There's gun violence in this country has become some normalized

1102
00:57:12,040 --> 00:57:15,719
Speaker 3: that like I heard school shooting at the top of

1103
00:57:15,760 --> 00:57:18,200
Speaker 3: this kind of when this story was breaking, and like

1104
00:57:18,280 --> 00:57:21,080
Speaker 3: it like barely bad in an eye over it. It's

1105
00:57:21,080 --> 00:57:23,080
Speaker 3: just it's become that normalized. That should be the thing

1106
00:57:23,080 --> 00:57:26,040
Speaker 3: that we're talking about, but we're not. We're getting roped

1107
00:57:26,040 --> 00:57:28,720
Speaker 3: into these like arbitrary conversations that have nothing to do

1108
00:57:28,760 --> 00:57:32,280
Speaker 3: with like the larger issue here, whether this.

1109
00:57:32,200 --> 00:57:34,640
Speaker 1: Person was trans or not. The fact that they identified

1110
00:57:34,720 --> 00:57:35,000
Speaker 1: is trans.

1111
00:57:35,080 --> 00:57:35,680
Speaker 5: At one point.

1112
00:57:36,120 --> 00:57:38,280
Speaker 3: Clearly there was other stuff going on, Like there's so

1113
00:57:38,360 --> 00:57:40,840
Speaker 3: many other things that should be the focus of the story,

1114
00:57:40,960 --> 00:57:44,560
Speaker 3: and unfortunately that's not what it's going to be. Well, actually, no,

1115
00:57:44,640 --> 00:57:47,320
Speaker 3: apparently it's going to be. I saw something that like

1116
00:57:47,840 --> 00:57:49,960
Speaker 3: was like Fox News is now like, oh, the left

1117
00:57:50,080 --> 00:57:54,160
Speaker 3: is mocking people for saying that we should pray for

1118
00:57:54,400 --> 00:57:56,760
Speaker 3: blah blah blah blah, and it was like, no, the

1119
00:57:56,840 --> 00:58:00,960
Speaker 3: mayor of Minneapolis just said, like, don't say thought some prayers.

1120
00:58:00,960 --> 00:58:03,760
Speaker 4: They were literally like praying this is insane, Like I

1121
00:58:03,800 --> 00:58:04,200
Speaker 4: don't know.

1122
00:58:04,560 --> 00:58:08,000
Speaker 1: Yeah, we are in some dark times, but Joey, I

1123
00:58:09,120 --> 00:58:11,880
Speaker 1: really appreciate you being a light in these dark times

1124
00:58:12,080 --> 00:58:17,000
Speaker 1: with follow your your thoughtful work. Where can folks follow you?

1125
00:58:17,480 --> 00:58:19,680
Speaker 1: Listen to what you've got going on, tell us all

1126
00:58:19,680 --> 00:58:20,160
Speaker 1: the things.

1127
00:58:20,600 --> 00:58:25,320
Speaker 3: Yeah, so if you want to listen to other things

1128
00:58:25,320 --> 00:58:27,480
Speaker 3: that I've worked on, you should definitely check out After

1129
00:58:27,480 --> 00:58:30,960
Speaker 3: your Lives. Like I mentioned, our first season was about

1130
00:58:31,480 --> 00:58:34,880
Speaker 3: Lealen Planco, who is a transgender woman who passed away

1131
00:58:34,920 --> 00:58:38,440
Speaker 3: at Breaker's prison. We go into a lot of the

1132
00:58:38,600 --> 00:58:41,840
Speaker 3: systems that led to her death because she really should

1133
00:58:41,880 --> 00:58:43,160
Speaker 3: not have died.

1134
00:58:43,400 --> 00:58:47,200
Speaker 4: There's so many things went wrong that should not have happened.

1135
00:58:47,280 --> 00:58:48,360
Speaker 1: And then the second.

1136
00:58:48,160 --> 00:58:50,600
Speaker 4: Season we took a little bit of a different route.

1137
00:58:50,640 --> 00:58:51,360
Speaker 4: It was about Marsha P.

1138
00:58:51,480 --> 00:58:57,360
Speaker 3: Johnson, whose eightieth birthday was recently. We definitely recommend checking

1139
00:58:57,400 --> 00:59:00,880
Speaker 3: that out if you're interested in queer history or just

1140
00:59:00,960 --> 00:59:05,080
Speaker 3: kind of like I will say, like tangent as you know,

1141
00:59:05,160 --> 00:59:07,920
Speaker 3: a queer person, as a transperson, I think like and

1142
00:59:07,960 --> 00:59:09,120
Speaker 3: as somebody who's also.

1143
00:59:08,960 --> 00:59:11,080
Speaker 1: Like just kind of like a history nerd.

1144
00:59:11,680 --> 00:59:14,000
Speaker 3: I find it really comforting to look back at these

1145
00:59:14,080 --> 00:59:18,440
Speaker 3: like stories of these like trans trailber lasers like Marshby

1146
00:59:18,480 --> 00:59:22,200
Speaker 3: Johnson and the like, looking at stone Wall, looking at

1147
00:59:22,240 --> 00:59:24,840
Speaker 3: what actually happened, looking at like how people rallied around

1148
00:59:24,840 --> 00:59:27,280
Speaker 3: people in the AIDS crisis. I think that gives me

1149
00:59:27,320 --> 00:59:28,800
Speaker 3: a lot of hope to be like, we're going to

1150
00:59:28,840 --> 00:59:30,280
Speaker 3: make it through this at the end of the day,

1151
00:59:30,400 --> 00:59:34,600
Speaker 3: Like our community is stronger than like the people.

1152
00:59:34,880 --> 00:59:38,360
Speaker 1: Trying to take us down. Ar We're gonna make it

1153
00:59:38,360 --> 00:59:38,640
Speaker 1: through it.

1154
00:59:38,640 --> 00:59:40,600
Speaker 4: But yeah, check out Afterlives.

1155
00:59:41,960 --> 00:59:46,720
Speaker 3: You can also hear me occasionally on stuff Mom Never

1156
00:59:46,800 --> 00:59:47,320
Speaker 3: Told You.

1157
00:59:49,240 --> 00:59:50,640
Speaker 1: I did an episode.

1158
00:59:50,200 --> 00:59:53,840
Speaker 3: Back in June about being non binary and some of

1159
00:59:53,960 --> 00:59:58,840
Speaker 3: like misconceptions around that. If you want to listen and yeah.

1160
00:59:58,880 --> 01:00:02,000
Speaker 3: If you want to fu follow me online, you can

1161
01:00:02,000 --> 01:00:04,000
Speaker 3: find me at pat not Pratt.

1162
01:00:04,240 --> 01:00:06,720
Speaker 1: That's p A T T n O T p r

1163
01:00:06,800 --> 01:00:08,240
Speaker 1: A T t I.

1164
01:00:08,680 --> 01:00:11,480
Speaker 3: That's my handle on Instagram and Twitter. I barely use

1165
01:00:11,520 --> 01:00:14,080
Speaker 3: Twitter anymore. I think it is also my Blue Sky,

1166
01:00:14,160 --> 01:00:15,840
Speaker 3: but I honestly don't even think I have the app

1167
01:00:15,840 --> 01:00:17,600
Speaker 3: downloaded anymore for blues side.

1168
01:00:18,880 --> 01:00:23,240
Speaker 1: But yeah, yeah, uh find me online, woo, follow Jolly

1169
01:00:23,320 --> 01:00:25,320
Speaker 1: and all the places. Thank you so much for listening.

1170
01:00:25,360 --> 01:00:32,760
Speaker 1: I will see you on the internet. Got a story

1171
01:00:32,800 --> 01:00:34,680
Speaker 1: about an interesting thing in tech, or just want to

1172
01:00:34,680 --> 01:00:37,040
Speaker 1: say hi, You can reach us at Hello at tegody

1173
01:00:37,080 --> 01:00:39,640
Speaker 1: dot com. You can also find transcripts for today's episode

1174
01:00:39,680 --> 01:00:41,880
Speaker 1: at tengody dot com. There Are No Girls on the

1175
01:00:41,880 --> 01:00:44,520
Speaker 1: Internet was created by me bridget Toad. It's a production

1176
01:00:44,560 --> 01:00:48,360
Speaker 1: of iHeartRadio and Unbossed creative Jonathan Strickland as our executive producer.

1177
01:00:48,680 --> 01:00:51,920
Speaker 1: Tarry Harrison is our producer and sound engineer. Michael Almado

1178
01:00:51,960 --> 01:00:55,520
Speaker 1: is our contributing producer. I'm your host, bridget Todd. If

1179
01:00:55,560 --> 01:00:57,360
Speaker 1: you want to help us grow, rate and review.

1180
01:00:57,200 --> 01:00:58,320
Speaker 5: Us on Apple Podcasts.

1181
01:00:59,000 --> 01:01:01,560
Speaker 1: For more podcasts from heart Radio, check out the iHeartRadio

1182
01:01:01,600 --> 01:01:03,880
Speaker 1: app Apple podcasts, or wherever you get your podcasts