The End. :(

Hello Everyone!! It’s the last week of senior projects which means that this will be my last blog post. Instead of simply discussing my research, which will be in my final paper, I thought I would reflect upon my experience these past 12 weeks.

My biggest takeaway is that reseach, especially when self-guided is extremely difficult. Before I started my reseach I wrote a 12 week plan of what I hoped to accomplish and looking back I only followed the schedule for  the first few weeks.

I started off with a broad research question and did not comprehend how difficult it would be to study everything I wanted in such a short time. One of the hardest parts of my research comprised of me having to exclude certain subsets of human trafficking for time’s sake. Everytime I delved deeper into the topic, a different angle of human trafficking stood out to me but I had to force myself to stay on track. Having no set steps or path to follow, the other hardest part of my project was defining my research question throughout these past 12 weeks. Every time I hit a road bump I had to adjust my whole project and take it in a new direction. Although it wasn’t ideal, it grew my appreciation for original reseach and helped me understand how complicated the issue of human trafficking is.

Another issue I took for granted during my research was the availability of data for me to run the tests I wanted to. I knew there would be some difficulty due to the illicit nature of the industry but certainly overestimated how much data there would be. I spent over two weeks just trying to find enough data to assess the relationship between trafficking and globalization. I went from thinking of data as a means to achieve an end but didn’t realize that effective data collection is something that has yet to be achieved in the field of human trafficking

 

I’m super grateful for the opportunity to have been able to conduct this research. I learned so much more about a topic that is important to me and I hope to continue my research not only in the summer but to also throughout my academic and professional career. I want to take a moment to thank everyone who’s helped me through the process inducing Ms. Belcher, Mr. Lizardo, Mr. Bhutoria, and Mr. Nooruddin. Each of these mentors took time out of their to help me with the many issues I dealt with while doing my research.

To everyone who plans to do a senior project or start their own independent research, the biggest thing I learned was that its ok if everything doesn’t go to plan. The most important thing is to be able to ask for help when needed and to overcome and adapt. Make sure you think about what you want your project/reseach to be about ahead of time so you can find mentors who are willing to help you along the way. Most importantly make sure it’s something you’re really passionate about because when things don’t go according to plan you won’t give up 🙂

I’ll also be presenting my research and sharing my final product on May 23 at the Hilton Doubletree in San Jose from 6:30-6:45 and you all are welcome to join.

What next?

Welcome back everyone! I started off this week by trying to learn more about current data collection methods for human trafficking. The first major issue I noticed was the lack of an agreed upon definition between countries, something also outlined in the UN report I read while doing my literature review. For instance, countries that define human trafficking as to only include sex trafficking don’t collect data on the other types on exploitation which are still considered human trafficking. Another reason for why there is such little data on victims of human trafficking is because of fear. Victims are afraid that they will face retaliation by traffickers or may even be deported if they were illegally brought into the country. The lack of protection for victims of human trafficking, especially in South Asia, make it less likely that victims will turn to their government and may even lead to victims being re- trafficked after escaping.

I also did a lot more research on the countries I looked at and compiled their progress and problems:

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Next week I hope to specifically look into how these 4 countries collect data and gain more insight into the region’s economy. I will be paying closer attention to Nepal which proved to be an outlier while I was doing the correlation study. Since the senior project comes to an end next week, I have been working on my research paper and can’t wait to share with you all, with more detail, what I’ve learn and found. See you next week 🙂

Less is always more? (not when it comes to data)

Although last week was spring break and I spent a little less time on my research, this past week has been an extremely important one in terms of results for my research. Just to recap, 2 weeks ago I finished my globalization scale and graphed my data which revealed that there was no correlation between human trafficking and economic globalization.

Most of my prior research demonstrated that there would be a reasonable link between economic globalization and human trafficking so I tried to find possibilities of error before I accepted that my hypothesis was wrong. The first issue was that of sample size. I could only find consistent data for 4 countries in South Asia: India, Nepal, Bangladesh, and Sri Lanka. Additionally, out of the countries that I could find data for, three of them are extremely small countries so it would be unreasonable to assume that globalization didn’t affect trafficking.

The second potential error I considered was that the index I made wasn’t an accurate representation of economic globalization. Therefore, I tried to do the analysis again with an established economic globalization index. Once again I got similar results; there was no correlation between economic globalization and human trafficking. I redid the analysis, this time instead of focusing on economic globalization I used an index that looked at globalization as a whole including factors such as political and social globalization but got the same result.

The next step was to detect any patterns in the 3 different trials I did and I finally found a possible explanation: when Nepal is taken out there is clear correlation between economic globalization and trafficking. While confirmation bias pushed me towards thinking that my hypothesis is finally right and that Nepal could just be an outlier it would be unreasonable to draw this conclusion. When we don’t consider Nepal we are effectively only analyzing three countries which isn’t substantial enough to support our hypothesis.

The most important lesson I learned this week was that one of the largest problems when it comes to combating human trafficking is our lack of knowledge about the industry. There is such little data when it comes to documenting the origin and destination of trafficked individuals which is integral to fixing the problem. For the rest of my research, instead of focusing on how trade deals and economic agreements can help decrease trafficking I will shift my focus to policies that South Asian countries can implement to facilitate data collection.

Proven Wrong?

Welcome back! This week was quite bittersweet. First things first I finished my “new and improved” globalization index and once again ran into a great deal of problems. Unlike last time, I decided to model my index after I collected the data so that I could adjust it accordingly. Speaking of data, I had great difficulty finding recent and organized data for all the countries in South Asia. I had to use the UN data which analyzed human trafficking from 2010 and 2011. Another problem was that different countries reported human trafficking data differently; some countries reported amount of cases currently being produced, some reported the number of victims reported, and others reported amount of prosecuted trafficking. Therefore I looked at most comment method of reporting the data in the UN study and decided to use the cases of human trafficking reported by each country. Unfortunately the only countries I could find that did this were India, Bangladesh, Sri Lanka, and Nepal.

After collecting all the data I was going to use I adjusted my globalization scale. First I had to find imports/exports/foreign direct investment as a % of GDP from 2011 since that was the most recent year for which I could find consistent statistics. I then weighted imports at 45%, exports at 25%, and foreign direct investment at 30%. Just like I took into account the larger economies of certain countries when creating my index I realized I should also take into account the fact that some countries, like India, have a comparatively larger population as well. Therefore, I divided the total cases reported in the UN document by the country’s total population.

Unfortunately, after I plotted the data, I saw that it completely disproved my hypothesis. There was no correlation between economic globalization and human trafficking. Next week I’m going to focus on trying to pinpoint the places I could have gone wrong and try to see if there is another way I can connect globalization and human trafficking.

Fixing Mistakes

Hi and welcome back! I’ve spent a lot of this week revisiting my globalization scale and finding ways to improve it. Something that has been bothering me about my old globalization scale is that it doesn’t take into the obvious fact that larger countries will have a greater number of exports and imports. For example India had $356,704,792,110 in imports while Bangladesh only had $48,058,710,040 in imports. This may have caused India to look a lot more globalized whereas this could simply be due to the fact that India has to import more goods to support its large population. Therefore my first change was using imports and exports as a percentage of GDP instead of the monetary value.

The second change to my new globalization scale will me made due to the difficulty in finding data. I reached out to my external advisor, Irfan Nooruddin, to see if he had access to databases that would help me find the data I needed. He connected me with Professor Vanessa Bouche at Texas Christian University who provided me with several databases that organize trafficking data. Unfortunately most of the data was a split up by region and not by country and the little data detailing what countries victims around the old came from had very little data about South Asian countries other than Afghanistan.

There is almost no data discussing how many human trafficking victims around the world originate from South Asia and categorize the data by country. Therefore it is extremely difficult for me to compare the number of victims that come out of each country and do a correlational analysis. Instead I am looking at the amount of victims that are currently being exploited in South Asia and breaking it up by country. Because I am looking at the flow of victims coming into the country I need to weigh the imports as a percentage of GDP higher than exports as a percentage of GDP. I will finish the new globalized scale next week and hope to perform the correlational analysis and have it ready for you all.

Numbers Numbers and even more Numbers

Hi everyone!! It’s been a pretty busy week for me in DC from building a snowman to sitting in a discussion analyzing the release of a new antiterrorism report.  This is also the first week where I didn’t focus on narrowing my research question and started compiling quantitative data. To start off, I finished my Globalization Index ! Because of the lack of data regarding the number of multinational corporations in host countries (a factor I wanted to include in my globalization index) the index only takes into account number of imports, exports, and direct foreign investment. Another big milestone was that I finally learned how to use google sheets! 🙂 Each step of calculation towards forming the index was taking too long because I did it individually at first, so I took it upon myself to learn how to use Google Sheets properly.

As I was making my globalization index there were a few problems that I encountered. First, the weightage I gave each factor was arbitrary. I weighed exports at 45% due to the fact that exports signify goods coming out of the country which may lead to an increase in the amount of humans being smuggled as well. It also means that workers in a country will have to make more goods and work longer hours to meet demand which could lead to deteriorating working conditions and more forced labour. I weighed foreign direct investment at 30% to determine if money invested in a country was being used to help develop the respective country and benefit individuals from all backgrounds or if it just created a higher demand for cheap labor. Finally, I weighed imports at 25% because I was more interested in what goods and services were coming out of the country than were coming in. If I were researching trafficking within Southeast Asia and not victims originating from this region, the weightage of the imports and exports would likely be switched.

The second problem I encountered was how exactly I was going to create this scale of globalization. All the models I looked at used different methods to create an in index and left me more confused than I was at the beginning so I tried my best to formulate my own.

  1. I transferred all my import/export and direct foreign investment data onto a spreadsheet.
  2. The import/export data was in US$ (thousands) so I just multiplied it by a 1,000 to match units with the direct foreign investment data which was just in US$
  3. Because the numbers were really big and therefore hard to work with, I divided all the numbers by a 100,000
  4. I then multiplied the import data by 0.25, the export data by 0.45 and direct foreign investment data by 0.3 in order to get the correct weightage for all the components

Now I have come to the part which is arguably one of the hardest parts of my research: finding trafficking statistics. So far I have also come across statistics which talk about victims of domestic trafficking and very little about how many foreign victims there are from a certain country. I will try to get access to more databases through my external advisors next week which I hope will give me the statistics I need. After I get the statistics I will perform a correlational study between the globalization score I assigned each country and the number of victims emerging from the respective country.

Taking a Closer Look

Welcome back! After hours of research, I have found a way to streamline and categorize my research. Instead of having a loose interpretation of the countries i’m studying, I have defined them as the countries that comprise the South Asian Association for Regional Cooperation (SAARC) which include Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan and Sri Lanka. There are two reasons for why I chose to use this block of nations. The first reason is that my advisors are more knowledgeable about this region which will help me when it comes to studying the  specific labor markets and governing policies of the regions. The second reason I chose to focus my research is that the SAARC is involved in many regional trade deals and similar economic policies with other nations which will make it easier to generalize my research.

Additionally after talking to my internal advisor this week, I have decided to focus on victims who have originated from South Asia  instead of those exploited within the region. Because my original purpose was to study how economic globalization affects human trafficking, it would be more logical to study how a country’s economic policy affects victims that originated from there.

I have started to form my scale for globalization as well. I finalized my inputs for the index : amount of exports, amount of imports, the amount of multinational corporations (corporations that have facilities and other assets in at least one country other than its home country), and direct foreign investment in these countries. As of now there are already several globalization indexes ranking countries but there are several reasons for why I chose to make my own. First, current globalization scales takes into account measures such as political and social globalization which I’m not measuring and studying. Second, these factors such as volume of trade and foreign investment are what I expect to directly impact trafficking.

I know this week’s blog post was kind of all over the place. I had to once again redefine my research and change how I approached the topic. Next week I hope to finish my globalization index and gather trafficking statistics for the nations I am studying. I’m also going to DC next week and will have a chance to meet with my external advisor and discuss how my project has been going so far. See you next week 🙂

Whats happening in Southeast Asia?

This week I focused on literature specifically discussing the issue of human trafficking in Southeast Asia. To my surprise, East Asia had greater available trafficking data compared to South Asia. I especially expected India to have a larger database on trafficking statistics due to its relative economic development in the region, but only Nepal had significant information on trafficking in its country. In East Asia most of the victims are regional meaning that they come from countries within East Asia; for example, victims in Thailand are mainly from Cambodia, Lao People’s Democratic Republic and Myanmar. However, a large number of victims from East Asia and South Asia have been found in all regions of the world including South America, the United States, and the Middle East.

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There are some regional differences in the types of trafficking between East Asia and South Asia. A great deal of trafficking in East Asia is sex exploitation with forced labor being the second most popular form of exploitation, especially in the fishing industry. On the other hand, in South Asia, it is expected that child labour is the most common form of exploitation with the other more common types including domestic servitude and child marriage.Screen Shot 2018-03-09 at 9.06.30 AM

When researching trafficking flows it occured to me that I need to define what I mean by studying human trafficking in Southeast Asia. Will I focus on individuals who are exploited in this region or victims who originated from this region. It would be more feasible to go with the first option because it will be easier to organize and study the trafficking data. If I go with the latter option I may have to specify another region of the world, such as the United States, and study how victims from Southeast Asia get trafficked there and how its fueled by globalization.

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Next week I plan to collect and organize all the human trafficking statistics specific to Southeast Asia and maybe the United States. I expect this to be pretty difficult because of the lack of data in South Asia and the discrepancies between convictions and the real volume of trafficking.

Digging Deeper

After doing some more research, I’ve come to the conclusion that I have no idea what I’m researching about. I started this week by trying to get a better idea of how human trafficking works around the world, it’s current patterns, causes, and the international legislation in place. I hoped that it would help me focus the purpose of my research so I could do a more in depth analysis on a certain aspect; instead, I found myself intrigued by new ideas: the patterns between migration and trafficking, how national development affects victim demographics, and an abundance of other ideas outlined throughout the paper.

Continue reading

Initial Research

To understand the intricacies behind the relationship of economics, globalization, and trafficking that we are trying to explore we first must understand what these individual entities are.

For the first week, I decided to research what countries are the most affected by human trafficking so that I could look at the treaties those countries are involved in. The first treaty I researched about was Trafficking Victims Protection Act.