Reaching out to the community – surveys

With less than a week before I fly back to America, I can safely say that I’m very happy with the work I have done here at Scotland’s Rural College. Over the last couple of weeks I have left the construction of my paper on the back burner for now so that I can dedicate time to collecting the data I need for it, which is really exciting! With the guidance of my advisor here at the college, I crafted a survey to send out to agricultural advisors in order to gather their opinions of food production and the environment. Dr. Barnes made a similar survey which has previously been sent out to farmers, and so the questions were only slightly modified in order for us to get parallel information which will let us directly compare the opinions of farmers and their advisors. In this way we can get a sense of whether these two groups, which should be working in tandem, actually see things the same, or if there are major differences which could be hindering the uptake of sustainable agricultural practices. The survey was sent off this morning, so now all that’s to be done is wait until people start responding! While I only have a few more days to work with Dr. Barnes in person, I will still be a part of the team even while back in America so that I can help analyse the data and then finish the paper I started less than 2 months ago. It will be incredibly satisfying to see this project through to the end and I am excited to see what data we get and what it can tell us about the future of sustainable farming.

Final Summary: Modeling Milkweed Population Dynamics

Since the summer research session is coming to an end and the first major phase to my project is almost “finished”, this seems like a good time to write my final post, wrapping up what I’ve been doing all summer, what has come from my work, and how this will transition into the next phases of the project. Just as a friendly reminder, this project is focussed on community ecology and population dynamics of the Common Milkweed, with the specific goal of modeling the size and demographic behavior of the population as a function of factors like herbivory and leaf chemistry. We use field-collected data and computational/statistical models in the R programming language to determine these relationships, that could inform management policies and conservation strategies.

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Data Wrangling

Near the conception of this project, I was part of several discussions on “data workflow” and other such monikers that allude to the crazy, messy world of what we call data. In a time when information and “big data” are valuable and only relatively recently tapped sources of knowledge, extracting insights from this messy world is a skill that seems like it just makes everything easier. So naturally, I was excited at the idea of being able to learn some of the techniques used to make sense of everything in the process of my summer research project. After all, when practicing science and statistics, there is a lot information to keep track of. Unfortunately that means there are that many more ways that all that information can get mixed up and jumbled around… I learned several important things about cleaning and managing data in the course of my project so far. [Read more…]

Organizations of all sizes making an impact in Uganda

One question I’ve pondered frequently is the tradeoff between working with smaller vs. larger organizations. While being a member of a small team allows you to have greater autonomy and responsibility, you may find your capacity and influence limited. The bureaucratic structure of big organizations may lead to inefficiency, though the weight and experience of a large institution can help you accomplish larger projects. Luckily, this summer, I didn’t have to choose: as an AidData Summer Fellow placed at UNICEF Uganda, I gained valuable experience working in an international NGO’s large country office while being supported by a small team at AidData in Williamsburg and Development Gateway in D.C.

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When you have to discard data

Last posting talked about the potential uncontrollable factors, and how researchers might handle them. This one will talk briefly about how a researcher might discern when to discard data for the validity of data analysis.

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