Author: Matt Liu, University of Wyoming Director of Debate Recently I worked with some of the Cheyenne East debaters to identify a need, brainstorm an idea, and produce an argument. Afterwards I realized that the way we took that idea from start to finish reflected a good research process, and it was worth writing about. This essay will walkthrough that process that we went through to show what a good research process looks like. Read the complete article below the fold. Looking for a more focused take on how to research well? Check out this introductory video by Professor Graham or this video-lecture by me.
Identifying a Need (Prioritization) This past weekend I worked with East at the Heart of The Rockies (Cheyenne Central) tournament. Once East’s policy teams were done at the tournament, we started looking at entries for our next tournament, Green River. We talked to other debaters and coaches to scout info about as many of the teams going as we could, and realized we’d be up against a territories social security aff, three Federal Jobs Guarantee affs, (infrastructure and Green New Deal), three teams debating for the first time, and one team reading a big social security reform aff. We felt really good about the territories SSI and FJG affs since we had prepped new strategies for the teams reading those affs at Central, so that left the new affs and the big social security expansion aff. We decided to focus our energy on the social security aff, since we knew what we needed, making sure we’d be free to work on the new aff at the tournament once we knew what it was. It’s not like East doesn’t have neg strats to social security, but we know not to underestimate our opponents. Researching a novel, specific argument is the edge we want to win close debates against talented rivals. I really liked how this went down. The East debaters could have just goofed off once they were out of the tournament, but instead they stayed focus and got a jump on their next tournament. By doing this while they were still at the tournament, they were able to take advantages of the resources around them to more effectively scout their opponents. Brainstorming an Idea (Conception) Once we identified what we needed to work on for the next tournament, we needed an idea. We pulled out our computers, started to do some introductory searches, and batted around some ideas. We didn’t want anything that was too repetitive with our existing neg strats against social security affs, so some ideas got binned because of that. Some ideas we struggled to come up with external impacts, so we put those ideas in the “parking lot” to come back to later. Working as a group and talking through the ideas was helpful, it meant that there was always someone there to red team an idea that sounded too good to be true, or find hidden value in an idea that wasn’t getting enough love. Social security is probably the hardest portion of the policy topic to research. One reason why is that the resolution calls for a substantial expansion of social security, but unlike a federal jobs guarantee or basic income, expanding social security has not really been a centerpiece of either party’s political agenda for quite some time. Proposals like the FJG and basic income have attracted a ton of attention recently because they have superstar advocates ranging from Bernie Sanders to Elon Musk, and that political attention translates to attention from media, think tanks, and scholars. Social security does attract attention, with the Trust Fund projected to run dry in the 2030’s, but the most mainstream proposals in the literature aren’t straightforward calls for expansion. In fact, most serious social security reform proposals are compromises that in some ways would reduce benefits to make the Trust Fund more sustainable. That doesn’t make the social security area of the topic impossible to research, but, it might make it a little more difficult. After running into a little trouble in my early brainstorming process because of this, I turned to an old friend for help: ChatGPT. A lot of educators are going to have a lot of feelings about ChatGPT, but to me, it’s a tool that if used skillfully can be helpful. Am I going to have ChatGPT write my arguments for me? Absolutely not (I want to win, after all). Will I use it in the brainstorming process? Definitely! Experience has taught me ChatGPT can direct my attention to cool ideas I might otherwise have missed and/or to ideas faster than I might have found them on my own. So I tossed ChatGPT a simple query: "Hi ChatGPT! Could you help me think of some reasons why expanding social security reform be a bad idea?" (I read somewhere that ChatGPT works better if you're polite, and although that's probably fake news, I can't think of a single DA to making sure speaking politely stays a habit for me, so I always do it). Now, I know that ChatGPT’s first couple of ideas are going to be pretty vanilla (mainstream, predictable, boring) and fairly repetitive, so after skimming the responses, I made my next move: asking for more ideas. "Thanks ChatGPT! What are some other ideas?" That still wasn't getting me where I wanted to go, so I tried: "What are some creative reasons expanding social security in the US might be bad?" That got close, but, no gold star ideas, so I ran it back: "Thanks again! Could you list some more ideas?" Not quite there yet, so I tried two more times: "What are some more ideas?" "Thanks! what are some more ideas?" And that last query hit gold: “Impact on Workforce Participation: Some argue that a generous social security system may lead to early retirements, reducing overall workforce participation and potentially affecting productivity and economic growth.” This idea clicked right away for me. First, it makes intuitive sense. Social security provides retirement income to seniors -- it's a social safety net for the elderly. The idea here is that the more attractive you make social security, the less attractive you make working for senior citizens. If the government will pay me bank for just existing, why go to my 9 to 5? I'm old and I'm tired, and I'd rather just hang up my hat. That's great for grandpa, but, not so hot for American industries. We're already in a post-COVID employment crunch, a spate of early retirements could be the straw on the camel's back for dozens of different economic sectors. Second, there's impact flexibility. Throw a dart at a board, pick an important industry, that's a DA. “Early retirements deck high skilled workers.” “Early retirements deck biotech.” “Early retirements deck manufacturing.” “Early retirements deck cybersecurity.” Etc, etc, ad infinitum: so many DA options! Also, tagging this DA is great: “boomers are key to cybersecurity” is a sentence I never thought I’d write. Getting the chance to vet this idea with a group of debaters while we were still at the tournament helped a ton. We were able to talk about what would make a good impact scenario, what kinds of uniqueness issues might get us in trouble, and we were able to come up with cool ideas to strengthen the argument. One East debater pointed out that older workers are extremely valuable because they have experience and skills, and that was a huge internal link boost and gave us ideas for search terms. This idea made sense, was strategic, and survived the group vetting process. Thus, the early retirements DA was born. Research (Execution) I was definitely not the only one working on this file, but, I was excited to research a cool new idea. When I got home and started working on it, I went through a familiar process: --envision idea that makes sense, --be happy, --start researching, --hit a discouraging bump in the road. When I started to research the link between social security and early retirements, everything was coming up COVID-clogged. Google would give me hundreds of articles about the relationship of retirements to COVID, with social security mentioned in a different context. The causal relationship was pandemic => retirement, and how SS plays into that, not what I was looking for: that social security spurs early retirements. This gave me a brief pause, and I momentarily wondered: “Is this idea a thing? Is it not a thing? Did I get this wrong?” Then I just added “-pandemic” to my search, eliminating any article talking about COVID. With that one small change (targeted to the specific research problem I was having, Google prioritizing articles about COVID), everything changed. I immediately got seven good PDFs in a row about the relationship between social security and retirements. (Why am I bothering to say that the first few results were PDFs? Because PDFs are often a shortcut for knowing something might be quality! Not every PDF is good, but it’s the format of professional publishing, whether think tanks or scholarly sources. People writing blogs in their parents’ basements definitely don’t often use the PDF format.) Not only did these PDFs have a lot of good cards, but they gave me the economic jargon I needed for good new search terms. Once I learned the language that experts writing about this subject used, that gave me search terms that unlocked truly monster articles. Why am I choosing to highlight the hiccups and roadblocks in my research process? Because everyone faces those, but this story is demonstrative of the fact that if you stick with it, and play around with your search terms, you’ll get there. Research is a lot of brute force, and then you hit one good article and when it rains it pours: you get search terms, bibliographies, and works cited replete with more sources you can go to. You can also use Google Scholar’s “cited by” function to look at who is citing that good article you found. The process might be tough at first, but hard work snowballs. If you’re still reading, I’m impressed! Thanks for sticking with me through the whole article. If you’re interested, here’s the first wave of work that got done on the Early Retirements DA. If you like that, you should join Team Wyoming. You can learn more about us here, and sign up here. Team Wyoming is the University of Wyoming's program to provide free supplemental debate coaching for high school students in the Mountain West. Go Pokes!
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