This visualization estimates the gender distribution of Ars Electronica submissions up to 2008, showing roughly 26.2% female contributors. It reads first names from a text file and uses the `gender_detector` Python library with the US dataset to guess each name’s gender, tallying results with `Counter` and `defaultdict`. The code prints cumulative counts, the percentage of women, and the most common female and male names after every 100 entries, revealing the skewed gender ratio and recurring contributor names.