Category: Article Annotations

Payton’s article, titled “City of Water: Port-au-Prince, Inequality, and the Social Meaning of Rain”, perfectly displays the connection between a person’s ability to access clean water and their place in the social hierarchy. Based around Port-au-Prince, Haiti, Payton’s study analyzes the environmental and political histories of the city in order to prove that the Haitian government used water resources as a form of power and control over their citizens. The Duvalier regime, which controlled Haiti in the 1970’s, noticed how valuable water resources were, due to the shortages and floods that the country was constantly dealing with, and decided to use them as a weapon to divide the different social classes. Decisions like these only split the country apart politically, leading to the eventual overthrow of the dictatorship in the 1980’s. 

The findings of this article prove a lot to be true about society. If the government in Haiti managed to use water access as a weapon against the people, what is to stop any other national government from doing the same thing? There are several countries worldwide that struggle with the same issues that Haiti faced in the 1970’s. All it takes is a corrupt politician to take control and people could completely lose access to one of their most basic needs. Beyond water though, governments could base class divisions off anything that suits their agenda, whether that’s education, food, or even money. 

It is also important to note that this study shows a different trend than most studies I have seen. More often than not, social hierarchy is used as a way to determine access to resources. Even in America, a person’s position in society can often factor into how easily they can get clean water. The interesting part about this article is that it shows the reverse happening, water access determining social status. Just like with corrupt governments, this trend could occur anywhere. That is why it is important to notice events like these so they can be prevented in the future. 

This article aims to uncover how family relationships affect Black land ownership through a specific example found in South Carolina. The researchers implemented ethnography and archival research to examine past and current land ownership situations between the Gullah/Geechee families. What they found was that the strong connections between family members, even if they were not related by blood, often pushed the people to speak up and fight against the governments that tried to limit their access to land. 

While some might see this as a powerful conclusion to the study, these results are not anything groundbreaking. It is already well known that most people work better in groups than on their own, so the idea that the people who lived with their family were more motivated to push back against the government is not a surprise. Plus, this study mainly focused on two families from the state of South Carolina. The exact results of the study could be due to factors such as the location where this study was conducted and the culture that surrounds that location.

Lisa Moore proves that, yet again, strong community ties are the key to bringing about change. Granted, there are some instances where people lose all hope in trying to fix their city simply because they know their government does not care. For the most part, however, cities where people have a strong sense of connection with their family or neighbors are the ones that end up making efforts to fix the problems that exist in their community. Flint, Michigan, would be a great example of this. All it takes to start a movement is for one person to decide if they are tired of living in their current conditions.

Moore, Lisa. “Gullah Geechee Families: Land and Culture.” Contemporary Rural Social Work Journal, vol. 9, no. 1, 2017, article 8

Katie Rawson and Trevor Munoz, the authors of this article, clearly made “data cleaning” the core topic. Specifically, the downsides to data cleaning. The main concerns that were brought up were the loss of validity and the reductiveness that can be caused by data cleaning. Without the complexity of data, which is lost in data cleaning, research studies become less accurate to real life, therefore less significant to the issue at hand. In the end, the authors propose a new approach to understanding complex data. This would consist of building systems that can explore the “strange” results instead of eliminating them completely. 

This seems to be a debate that is not exactly new to research fields. I know this because the author’s purpose was not to completely get rid of data cleaning, but to change how it is done. A change in the way data cleaning is conducted was first suggested whenever the authors mentioned how harmful the current practice is. The only main alteration that is brought up is the creation of a new system that values the different and unique qualities of data. This is not a new revelation, since data cleaning has been a valuable part of research for years. However, the article still holds a significant argument, proving that data cleaning is a piece of an old system that is in dire need of an update. This is all done without entirely bashing data cleaning as a practice. 

While I may not know much about data cleaning and the arguments against it, I know this is a controversial topic, since data cleaning has long been used to improve data quality after a study is conducted. Fortunately, the way this article was written gets the point across while not attempting to take data cleaning off the list of research practices. Now, new researchers who read this article can understand the downfalls of data cleaning without ignoring its full benefits. 

If you asked the average person 10 years ago what they thought about artificial intelligence, most people would either immediately think about the robots from the Terminator or not understand what artificial intelligence actually is. By definition, artificial intelligence is the capacity of a computer program to execute functions that are normally related to human intelligence. In recent years, artificial intelligence programs like ChatGPT have become very popular as programmers are racing to improve the effectiveness of AI. This has also sparked a lot of debate about when and where AI should be properly used, like in school, for example. Luckily, many researchers have began to look into issues revolving around AI. An article titled “ChatGPT Goes to College” does a great job at showing just how far along we are on the path tp full AI integration. 

This study on ChatGPT was originally conducted in order to understand students’ views on artificial intelligence and its usefulness. The team created a survey that asked various questions such as how often they use ChatGPT in a school setting. Over 700 college students were asked these questions. In the end, the results showed that the introduction of ChatGPT did not directly cause the number of “cheaters” to increase, it merely allowed students who already had no problem with cheating to get assignments done in a crunch. This clearly shows that AI is not at the point where it is a concern for all students, as 54% of the students interviewed claimed that they have not yet used ChatGPT for school assignments. 

One of my first thoughts on the article was that it did a great job at making sure the results were not up for interpretation. The questions asked made sure to include several factors for the study, such as usage, reasoning, and effectiveness of usage. While this article did not end the debate on AI usage in school, it showed that there is still time to guide students on using artificial intelligence programs such as ChatGPT. The only problem with this study is that it was not widespread enough to show how true those results are for the rest of the country. 

The end of the study did catch me off guard at first. I have not done much research in regard to artificial intelligence in school, but even back in my senior year of high school, I began hearing several of my classmates talk about using AI to complete their assignments. These were also students who would not normally cheat in class. I would have expected the number of people who are comfortable with cheating to rise after ChatGPT. Now, these results may not be totally accurate compared to the rest of America, since the study had a few limitations to it, but I believe the study’s future implications are more important. We are at a time now when AI is still new, and not all students are using it in their everyday lives. This is the perfect opportunity for teachers to educate students on proper usage of artificial intelligence before it is too late. 

Works Cited 

Cavazos, Jenel T., et al. “ChatGPT Goes to College: Exploring Student Perspectives on Artificial Intelligence in the Classroom.” Teaching of Psychology, vol. 1, 7 Aug. 2024, www.researchgate.net/publication/382936523_ChatGPT_Goes_to_College_Exploring_Student_Perspectives_on_Artificial_Intelligence_in_the_Classroom, https://doi.org/10.1177/00986283241268829.