IJustCame.org offers porn for the greater good. This website donates a penny to charity each time you get off. The new porn website is where you can watch adult videos and masturbate for a good cause. But here’s the catch; each user is limited to 2 pornos per day with 15-minute breather between each video.
Stanford University undergrads Adam Lee and James Cook came up with the idea for the porn website after they spent “a drunk night partying at frats.” Lee told the Huffington Post, “Originally, we were trying to build a Tinder for lunch, for people who didn’t want to eat alone.” So basically, it was a full 180 switch from a lunch date to porn for a good cause.
Lee said that before they officially launched the website, they anonymously tested it and “in a very short time” raised over $1,000. “You can do the math on how many scenes were viewed, but that gave us the confidence to move forward.”
Currently, the duo is funding the donations from their own pockets but according to Cook, IJustCame.org will get sponsors soon. And Lee believes that their website could potentially donate millions of dollars to charity every year if everything goes according to plan.
The following charities split the masturbation money:
1. Movember Foundation – global charity that funds testicular cancer programs.
2. Ovarian Cancer Research Fund – charity in the US that funds ovarian cancer research to better diagnose, treat, and ultimately cure ovarian cancer.
3. Joyful Heart Foundation – an organisation whose mission is to heal, educate and empower victims of sexual assault, domestic violence and child abuse.
So remember that you can make a difference just by getting off. Will you make this world a better place?
3 thoughts on “Masturbate for humankind with a porn site that donates money to charity”
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relationship and robust lead-lag relationship.
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embeddings, which build on exponential family to capture how the meanings of words change over time.
To acquire the subject embeddings and phrase embeddings, we comply with (Dieng et al, 2019) to apply DETM on the ACL dataset with
a total of fifty subjects. To train the model, a novel dataset is
collected and annotated, consisting of six manipulation relationship courses and thirteen device classes.
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