In Game of Thrones most recent episode (S8 E2), teenage heroin Arya Stark (played by Maisie Williams) was portrayed having her first sexual experience, a highly anticipated moment for fans. Aside from the artistic and dramatic effects of a sexually enticing moment, I'd like to highlight the potentially devastating effects of portraying sexuality in young characters in films.
How old is Arya Stark?
According to the books, she'd be 18 by Season 8. Source.
How old is Maisie Williams?
22. (Her birthday is April 15, if you want to send flowers.)
An 18 year old consented to have sex, why the conflagration?
My issue is that in all likeliness, most of GOT's 17.4 million viewers don't know Arya's or Masie's age off-hand. For the time between their viewing the content and the viewer researching these ages, there is an image of an underage person choosing to have sex with someone well above their age. This can be devastating to adults who are coping with non-offending pedophelia, a condition which affects 1-3% of U.S. men (approximately 1.18 million to 3.54 million men). Visual and audio stimulation of minors – especially those not explicitly pornographic – can be toxically triggering for these people, who unsurprisingly, feel discouraged from seeking professional help.
The relationship between sexual interests and portrayals in film and TV is extremely related. To demonstrate, the worldwide Google Trends results for queries relating to Arya Stark, her age, and her sexuality in the hours following the release of S8 E2 are shown below. The scores for Arya Stark Nude [4-21] has spiked since the release of the episode.
What if Arya Stark would have said "I'm 18 years old, I'm adult enough to do as I please."
Without doubt, it would have likely strengthened the passion of Arya's moment and empowered her in the moments following. But more importantly, it would help the show's millions of viewers by providing clarity to consent – and show how verbal language surrounding consent can be empowering, sincere, and sexy.
The makers of Game of Thrones missed a valuable opportunity in this past episode. I challenge you to find solutions in content you're creating that are aimed at similar objectives of portraying verbalized consent, thus sincerity.
1. Seto, M.C. (2013). Internet sex offenders. Washington, DC: American Psychological Association.
2. Howitt, D. (1995). Pornography and the paedophile: Is it criminogenic?. British Journal of Medical Psychology, 68(1), 15-27.
My article "Opening the Stage Door for Big Data in Broadway — Building Databases from unstructured text using Machine Learning."
I've spent a good portion of my summer devising a complex machine learning algorithm which extracts data for all Broadway shows, ever. This article summarizes my approach, and provides explanations, pitfalls, and insights. Also, the code for this algorithm is available through the article!
Scrapped data, no statistical analysis conducted.
So far this summer, I've been researching the mathematics and data science of dynamic modelling. My goal is to develop a model for maximization of revenue and attendance for Broadway shows. Articulated in the proposal below are the speculated means for which I hope to accomplish this undertaking.
– Give it a read?
– Let me know what you think?
– Feedback or ideas are warmly welcome!
The following interactive graph describes the revenue performance of last week's Broadway shows. Try clicking on the graph and see what comes of it. This is a learning experience for me so I appreciate all feedback you can provide! Send me an email if something stands out: firstname.lastname@example.org
Weekly Gross versus Capacity (Week of July 1, 2018
The x axis describes the percentage of occupied of seats for a production. A value of "80" would connote that the production full-filled 80% of their seats. A score above 100% is achieved by selling standing room.
The y axis describes the weekly gross of a production for that week's performance. This includes all sales for that week's performances, regardless of when tickets were purchased. For example, if someone purchased tickets 2 months ago for a show within this week, that sale would be included in this week's data set.
The size of each point describes total attendance of that data point for the week. Of note, the largest (grey) point describes Harry Potter and the Cursed Child.
Some extra info: