1. Proposal

In this project we propose to carry out a datat intensive analysis of the situation in the Argentina astronomical workforce regarding the gender balance.

We make use of several tools and techniques, including:

  • hypothesis testing

  • machine learning

  • word embeddings

  • web scraping

  • statistical analysis

  • model selection and assessment

We aim at leveraging open data to produce our results, and we publish the full stack of the data reduction and analysis pipeline so that anyone can use the data and reproduce the results or revamp the analysis.

This way, our results and conclusions can be revised by researchers in the data science or gendeer studies communities.

1.1. Methods

We propose the following working hypothesis: In Argentina, in the profesional astronomical community, there is a segregation effect in gender due to structural causes and independent of personal choices. This segregation or gender bias leads to a noticeable unfair availability of opportunities in the development of careers for women and men.

1.2. Data analysis

Statistical analysis of the following aspects on the astronomy career in Argentina:

  • Gender representation in the academic career in Universities

  • Gender representation in scholarships (CONICET)

  • Gender representation in permanent positions (CIC, CONICET)

  • Gender differences in scientific production metrics

  • Gender differences in the academic performance in Universities