Inequality of Education with Respect to Geopolitics

Story

What Promotes Education? Mountains or the Soviet Union: A Data Analysis on the Inequality of Education with respect to Geopolitics.

December 1991, the fall of the Soviet Union shook all the countries under it. December 2021, the effects of the Union are still visible throughout the fallen empire, for the better or for the worse. The education inequality might be at its highest in Afghanistan, over the mountains separating the old soviet union from the rest of the world, but the inequality of education index drops to <0.05 (on a scale of 0-1). What does that suggest? What could we deduct from this data? But before all, what do mountains have to do with the education equality rates? It is not unknown that the old soviet union is all surrounded by mountains. This might look very unrelated, but it suggests that invading beyond the mountains was a harder task to achieve. And bound in between the glory of the mountains, they established their own proper educational regulations, including a system named Likbez. The aim of this system was to eradicate all kinds of illiteracy throughout the union, and to achieve that goal they built up a specific schooling system. So even after a decade, the trail of this system can be seen in the almost nonexistent education inequality rates in all countries previously occupied by the soviet union, where the literacy rates have all stayed above 98%. This is because the neighboring countries beyond the mountains had more chances of interacting with one another and thus propagating their education system. On the other hand, since the countries previously under the soviet union were all separated by these natural borders from the rest of the world, their only interaction were among themselves which could explain the difference in the inequality between this region and the countries beyond the mountains. This could also explain why the literacy rate is the same for that region compared to the others since they were all part of one education system, and the education systems have not varied much since.

However, despite all, it is important to consider that the factors taken into consideration for this comparison of the inequality could be considered flawed, since only literacy is taken into account, and indeed literacy is not the only defining part of education.

What inspired you to go in this direction?

We were all very interested with the topic of “education” since we are all from different origins whose education systems and rates are absurdly different. So we first started by looking at the data from the inequality of education throughout the world through the 20th centuries and the 21st century. Among all the abnormalities that we discovered, realizing that the lowest education inequality rate was in Uzbekistan for a decade surprised us most. Looking more into the neighboring countries, we realized that these low rates were a common occurrence up until the borders of Iran, Afghanistan, Mongolia, Spain. These trends in the equality of education mostly follow up. We then looked at the history and the geopolitical positions of these neighboring countries and we realized that there were mainly 2 similar causations for these rates: almost all these countries were previously invaded by the USSSR , and they were all separated by the mountains from the rest of the world. The mountains could explain the similarities in the education systems since before the world of the internet , propagating new information could only be done through travelling. And by looking at the soviet union history we found out certain education systems were imposed.

Behind the Story: Our Data Analysis

What did you do with the data? For example, how did you manipulate the data? First we searched up different data around the topic of education until one caught our attention, we then verified the reliability of the data through looking at the sources. The, getting help from chatGPT and excel we made a row per country and each country had a column for each year in between 2010 and 2021, and we took this data and we matched the data with ISO3 code which then we plotted it into a map.

What are your data sources?

Roser, Max, and Esteban Ortiz-ospina. “Literacy.” Our World in Data, 20 Sept. 2018, ourworldindata.org/literacy.

“Inequality in Education.” Our World in Data, ourworldindata.org/grapher/inequality-in-education

“Soviet Union on World Map.” Burning Compass, www.burningcompass.com/on-world-map/soviet-union-on-world-map.html#google_vignette

“Женщина! Учись грамоте!.. - 20-30 роки ХХ сторіччя - Плакати - Фотоальбом - Історія України.” Ukrhist.at.ua, ukrhist.at.ua/photo/4-0-16

Grenoble, Lenore (2003). Language Policy in the Soviet Union. Boston: Kluwer Academic Publishers “Free Topographic Maps, Elevation, Terrain.” Topographic Maps, en-ca.topographic-map.com/?fbclid=IwAR3Kqb5N8kUtu1q_G9XYkqPSnPczmFQHxKRKN579pzUBo-n97xkLvNVs0gk

How did you use ChatGPT?

Chat GPT was mainly used to answer questions related to coding and specific information about libraries that we did not have any experience with, such as Selenium and plotly.express. Although the accuracy of the answers were not always perfect, this tool was extremely useful to generate a draft code or to point where in the documentation we should look for answers.

What we learned

Tell us something about challenges you overcame, new knowledge or skills acquired, etc. Firstly, from a coding perspective, we learned how to make gif, interactive graphs and a website as well as how to work with Google Colab. Secondly, we expanded our geopolitical knowledge as well as history, through looking at the effects of natural terrains and politics on our new world such as current educational systems. Thirdly, as science students, we had to learn how to navigate between the two worlds of science and social science.