Today I met with Professor Robinson for a quick half hour meeting. This was the last of our regularly scheduled weekly meetings. We debriefed about both the conference last week, and the presentation I had gave early today in class. She provided me with feedback which ranged from general academic presentation tips, to technical details that I had missed in my tables. She also sent me an email with a list of all of her comments so that I could refer to them moving forward.
We also decided that I would get her a draft of my final paper by next Monday ( 4/30/18) so that should would have ample time to read over it and provide feedback while still leaving me time to incorporate that feedback before the due date. I thanked her again for volunteering her time this year to mentor me throughout this project, and we agreed that I would come back and visit often over the next two years whenever I either had a question about statistics or just something interesting about remittances that I wanted to share.
Today I met with Professor Robinson for just over half an hour. I had just left Professor Assenov’s office, and so I had a solid idea of what I needed to go moving forward with the project. Therefore, most of our meeting today consisted of her helping me figure out how to actually go about creating the types of tables and graphs that Professor Assenov had suggested. Additionally, Professor Robinson answered many of the questions that I had about the upcoming presentations, both about what to include in the poster and about how to structure my presentation. Lastly, we just reviewed the meaning of all of the numbers that I had generated with my analysis to ensure that I was not misinterpreting or misrepresenting anything. By tonight I will have sent her a draft of my poster for her to take a look at and provide feedback on in time for the poster conference on Friday.
Today I had my final meeting with Professor Assenov at the CTRL office. Since the purpose of our meetings was primarily to help me get through the regressions in Stata, and since I finished that last week, our meeting today was only about 20 minutes. As I mentioned in my previous post, I have been working this week to represent my findings in a coherent manner. Today, with Professor Assenov, I was able finalize my conception of what I needed to include in both the poster and in the Powerpoint presentation. His main suggestion was to use the log of my capital flow data in the scatter plots, because that way they would be much clearer to a casual observer trying to quickly identify patterns.
Last Tuesday Professor Robinson and I had to have our meeting over Skype. The meeting lasted just over an hour. I showed her all of my results from the analysis I had done the previous week, and we started identifying key relationships and interesting correlations. We began discussing how best to represent the data that I now had in clear and concise ways for the upcoming class and poster presentations. Partly do to the fact that we were not in the same room, it was slightly difficult for me to get a clear understanding of how to create all of the necessary models in Stata, and so there was fewer substantive outcomes actually produced in this meeting than normal. That being said, I certainly left with an understanding of what types of models I would need to create. I have been working on figuring out these logistics in the past week.
Tuesday, April 2018
I met with Professor Robinson today over Skype for just over an hour. In this meeting we were able to sort out a number of small details (mostly errors with Stata commands or data formatting), and I now have a finished version of all of my regressions. Additionally we begin exploring ways to represent the data quickly and simply for the updated analysis section of the final paper. I learned how to create general descriptive statistics tables, as well as a complete correlation table for all of my variables to put at the beginning of the section. We also picked out a number of scatter plot binary correlations that may prove helpful as visual aids for either the analysis section of the upcoming presentations. Moving forward I am meeting again with Professor Assenov from the CTRL lab to have him look over my data and results and make sure everything seems consistent and that there are no errors. After that, I am only left with rewriting the analysis section to include the updated numbers and whatever visuals I decide on as most important.
The readings from seminar seven concerning non-canonical and marginalized scholarship contained ideas with what I was certainly familiar, but had never before seen manifested in this way. I believe it is fair to say that the fundamental argument of the Decolonizing our Minds movement at SOAS can be boiled down to the common tropes of systemic racial inequality. What seems to make this movement unique is that it specifically critiques the academic world, which is typically thought of, and certainly sees itself as, more progressive. Ultimately I was underwhelmed by the arguments from the Decolonizing our Minds movement, not because I disagree with their critiques, but because they did not seem to offer, at least from the article, an innovative solution. Their initial argument seems to have been to remove the white scholars, or at least most of them, from the curriculum because they represent, by virtue of their identities, historic systems of oppression and marginalization. When professor Malik confronts the students however, they reportedly backdown and claim alternatively that traditional white scholars should be taught, just within a critical framework – one that makes aware their systemic privileges and personal failings, moral or otherwise. Whereas the first argument seemed like an over reaction, this compromise does not seem to be saying much at all. It seems to me that a critical approach should be – and more often than not is – applied to all scholars and ideas presented students, at least in higher education settings. So while I certainly do not disagree with the students claims, I fail to see how this argument is original, or how it particularly pertains to the white scholarship antagonists that the whole movement is founded on “decolonizing” themselves from.
Professor Morris, in my opinion, makes a much more interesting argument in his study of the historical account of American sociology, and particularly W.E.B Du Bois. While neither professor Morris, nor any rational person, denies that race almost certainly played a part in Du Bois’ marginalization, Morris argues that an equally important factor was the heterodox nature of Du Bois’ and his schools, claims. This argument highlights a flaw within the academic elite which has likely remains much more salient today than outright racism. I am in no way claiming that racism has entirely subsided from the academic world, rather that this paradigm of orthodoxy remains both more prevalent, and less understood than racism. I have been particularly exposed to this in my economics courses. Any findings which challenge commonly held beliefs have historically required mountains of data to support them, while findings which support the orthodoxy are overly inflated. The example of structural adjustment programs in development provides a clear example of this. It is because economics has historically been so reluctant to accept challenges to the orthodoxy that I will have to be cautious in the future to not fall into the same traps. While certainly not all critiques will be paradigm shifting, it will be important for me to keep myself open to the possibility.
Tuesday, March 27 2018
This meeting lasted just over an hour. Professor Robinson and I began to actually work through the coding for the regressions in Stata. I had tried to begin this process the week before with someone from the CTRL lab, but we ran into a few issues regarding the data sheet itself, and thus could not move forward, and there was nothing substantial to report. So between that last meeting and today’s meeting I have been fixing up those mistakes, which included converting all gross data into per capita numbers, changing the original indicators (Freedom House and PRIO) into bivariate. Once these changes were made I was able to actually work through the regressions with Professor Field. We quickly decided that I would also need to linearly interpolate the data for my dependent variables which only appear every 4-5 years at best (most likely from national censuses). The reason for this, even though it is in effect “making up data” is that without interpolating, given the limited availability of many of the other indicators, my cases drop from over 1200 to 68. The reason for this is that Stata will only run the regression if every line of data for a case is filled. While 68 is still enough cases to perform the statistical tests, I decided that it will still be beneficial to run the regressions on interpolated data also (I will certainly keep the original regressions with the 68 cases, if for no other reason than to compare). Because my DV’s (Gini index and Poverty percentages) change so little, and so linearly, I decided that linear interpolation will bring more validity to the project by way of adding hundreds of additional cases than it detracts from that validity by “making up data.” Regardless of this addition, the meeting went very well. I now understand all of what I need to to perform regressions in Stata with panel data, and a few other tests which can be useful, such as bivariate correlation for my DV’s.
After this meeting I feel confident moving forward that I can finish up the ‘meat’ of the project in the next week. I will interpolate the data and perform those same regressions that I did with my original data. Once this is done, all that is left is the interpret the results and write up the analysis – certainly not a small task, but one that I am familiar with and feel comfortable doing independently. Once this is done I will begin revising all of the sections we have been working on all year, and I will synthesize them into a complete paper.