Inspiration:

I'm a data science enthusiast, but I'm also passionate about international relations. For this hackathon, I chose the activism track because it lets me connect technology with international relations. I like to research about developing countries and their position on the global stage, so I decided to work with United Nations data. One of the important issues in developing countries is human rights, so I chose to investigate how each member of the United Nations voted on human rights resolutions in comparison to their human rights record.

What It Does:

My project is an analysis of how nations voted on human rights resolutions in the United Nations versus the final outcome. Then, I compare the representation of a nation's choices to their human rights ranking. Do the choices of nations with worse human rights records get represented or do the choices of nations with high human rights scores get represented? Since there are more nations with worse human rights scores, my project will suggest the implementation of a priority system in the United Nations General Assembly.

How I Built It:

I used the Python Pandas library to clean and process my data and create the final tables showing my results. I used infogram to create a presentation and compare human rights scores to how nations voted in the UN General Assembly.

How I Built It:

The major challenge I ran into is creating the tables to show my final results. It was difficult to navigate through the four groups as they each had different number of options, so a for loop wasn't possible leading me to duplicate the code with minor edits.

What I Learned:

Groups 1 and 2, or countries with high human rights scores, have the most resolutions they either voted to fail or abstained from voting that for passed, for an average of 223 resolutions versus 50 resolutions for groups 3 and 4, or groups with the worst human rights scores. Since there are less nations in groups 1 and 2, their choices are not represented even though they should be given priority on human rights resolutions because of their high human rights scores. In the future, as the human rights violations per nation increase, more nations will defend human rights violations, leading to positive human rights resolutions not being passed and negative ones will be passed. Therefore, the United Nations should reconsider their voting system by candidate attribute by giving priority to nations who show no bias or have a positive record in that attribute.

What's Next For Assessing United Nations Human Rights Resolutions:

An analysis of economic characteristics of member nations versus how they voted on economic development resolutions in the United Nations General Assembly.

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