Jamie Hare

Decision Scientist and Religious Studies PhD

I am a decision scientist and religious studies PhD living in Decatur, Georgia. I am an experienced researcher, writer, editor, teacher, and project manager.

Prior to moving to Georgia, I spent five years as a project manager at an internationally operating, progressive non-profit institution for civic education. My primary responsibilities concerned socio-ecological transformation, particularly in relationship to the Global South.

My educational background is in South Asian religious studies and culminated in a PhD. Read more about my dissertation and scholarly publications on my research page.

Latest Blog Posts

Don't Say Gay

I wrote an article on the current spate of “anti-woke” laws in the United States for the Rosa Luxemburg Stiftung’s New York office: For some socialists, this debate might seem like a distraction, an aspect of the culture wars pitting the neoliberal establishment against the Christian nationalist right, but these laws have real material consequences for the overwhelming majority of the working class who are women, people of color, or queer.

Alberrative parturine of eggliness

So I’ve been learning about neural networks and how to use TensorFlow. I wanted to get in on the trend of using recurrent neural networks to generate predictive texts (inspired by Jacqueline Nolis' banned license plate generator), so I trained one to create text in the style of James Joyce’s Ulysses. Here’s a sample. I think it’s a pretty good approximation of the original. Stephen, he had murdered to.

Atlanta Sports

As part of my ongoing effort to learn Python for data analysis, I created this chart summarizing the relative performance of Atlanta’s major league sports teams since the Hawks moved to Atlanta in 1968. Atlanta has not consistently had an NHL team during this time period, and Atlanta’s MLS team is a much more recent addition. In order to facilitate comparisons across sports, ties have been disregarded. The data is presented here as a 10-year rolling average in order to smooth out spikes from one season to the next.

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