An academic article is a persuasive text. You’re trying to convince people of the series of points they may or not have believed before reading your article. In doing so, you want them to save their time on extraneous information and make it easy for them to understand what you are trying to convey. That is, what is your point?
I took a fantastic online class from a Wall Street Journal journalist. I had written academic articles for over a decade before watching this course. However, the course made me think about points more clearly than I had previously. There’s a tendency in some corners of the academic world to need clarification about the point you’re trying to make. Let me get to the point: your job in an academic article is to sequence a series of points that make a larger point. That leads to sharp writing.
Every paragraph needs to have a point to make. Let’s go back to our introduction. As discussed in the previous section, the introduction consists of approximately five paragraphs. The paragraphs are structured in an hourglass fashion.
The first paragraph conveys the following point: this is an important topic, and you should consider this research question. Second paragraph: most people have been thinking about the problem this way, but you should think about it my way. Third paragraph: I have done rigorous work to convince you that my argument is correct. Fourth paragraph: this is what I found. Fifth paragraph: this is why it matters.
In one of my papers that I’m working on to demonstrate how this might be done, we can think of the big points of the paragraph as a topic sentence.
Understanding the process by which fundamental scientific discoveries are commercialized is vital to researchers and policymakers.
Most research has focused on understanding the contextual factors that may reduce friction in commercializing science without considering the commercial potential of these discoveries.
We develop mechanisms for extracting the latent commercial potential of scientific discovery using machine learning and crowdsourcing.
Our crowdsourcing measure significantly predicts eventual commercialization, other than machine learning measures.
Our approach can help researchers better understand where commercial potential lies and the friction prevented from being realized.
Now that we have the main points we want to convey in each paragraph, we can think about how we will support the main points with subpoints.
Let us now expand on the main point of the first paragraph.
Understanding the process by which scientific discoveries are commercialized is important to researchers and policymakers.
To expand on this point, what additional points may make people believe this statement?
Here’s the exciting part, make as many points as you can, and we can organize them later.
Now that we have these points let’s go through them and decide which ones are relevant to this paragraph and the point it is trying to make, those that are relevant but not to this paragraph, and those that are not relevant to any paragraph in this manuscript.
Once we have done this, the next step is to order the relevant points to make our main point the strongest it can be. There are several different orderings of these points. However, the following is the most reasonable sequence.
Organizing paragraphs around a single point makes it much easier to understand for a reader. In fact, it allows them to skim the manuscript and know precisely what is going on without having to reread the sentence over again.
The metric you want to use is: can people read the paragraph and know exactly what is going on without rereading it. That is when you know that you have written a strong paragraph that gets your point across.