Research papers follow a regular structure that helps you find what matters for your project. Most papers have the following sections:

• Abstract – the summary of the study and its findings.
• Literature – a sketch of background information and where the study’s hypothesis fits in this literature.
• Methodology – a breakdown of how the study was conducted.
• Results – a technical breakdown of the study’s data.
• Discussion – what the data means.
• Conclusion – draws meaning and discusses weaknesses in the study.

Depending on why you read the research paper, the Abstract, Literature, Discussion, and Conclusion sections may be the most useful for you. Methodology and Results sections target people who want to replicate the study for peer review, but for everyone else, the data can be limited or esoteric. You’ll find a lot of statistical analysis here. I find the Literature and Discussion sections of studies the most useful when I write books or articles. Literature provides context and shows patterns. Discussion focuses on how the study fits into this context, refuting, confirming, expanding, or adding nuance. Often this sections offer the “large picture” of the research, such as how it can be generalized or not.

Generalization requires caution. A study is usually limited in its context based on its sample size and methodology. Sample sizes can be designed to generalized to the greater population, but sample sizes have to be a cross section of the greater population to offer such lessons. For example, David Blanchflower studied human happiness trends. In his study, he looked at data samples collected from 145 countries with the data sets ranging from 15 year-olds to over 70. In the study, he points out exceptions to the age pattern trends the data holds, such as with the US. His study found a U-shape happiness curve common across cultures and socio-economonics. Namely, people’s happiness levels hits its lowest point at 47 years old. After this point, happiness gradually increases until it reaches the same levels as teen and early adulthood at around 70 years of age. His study suggests this is a universal human experience. The data also shows women tend to be less happy across the same U-shaped life cycle than men.

Blanchflower’s sample size aims at generalizing across humanity because of the wide, cross-cultural and cross-socioeconomic groups he pulls from. Even with data sets like this, there’s exceptions to the trend. The most danger comes from generalizing from too-small or too-specific sample sizes. Good studies will express this problem in their Conclusion or Discussion sections.

Research papers aim to minimize common human cognitive biases such as confirmation bias and the Dunning-Kruger Effect. Confirmation bias happens when you disregard data that fails to support your idea. The Dunning-Kruger Effect happens when people of low capability overestimate their knowledge and understanding. When reading and using research papers, beware these cognitive biases within yourself. It’s easy to disregard information that contradicts your viewpoint. Likewise, you may overestimate how well you understand the research paper you read. Confirmation bias and Dunning-Kruger Effect become pernicious when you deal with ideas related to identity. The ego resists anything that challenges it and its ideas of reality. The more certain you feel about something, the more you need to doubt that something. Certainty warns of cognitive bias. So when you encounter research that supports your idea, keep looking. Don’t discounter confirmation of your thinking–that too is a cognitive failure–but nor should you be certain and closed in your thinking.

Science is always adjusting and refining itself. Future studies find flaws in past studies. History too is always changing as new information appears. While many people talk about “revisionism”, these people don’t understand how science and history works. As new facts come to light and are confirmed to be facts, it would be foolish not to shift thinking. New facts doesn’t discount the value of old ways of thinking, however. Old methods of thinking provides a timeline for how thoughts about a certain idea develop. Think about how the earth was considered round, then flat, then round again across history.

Why Does Research Matter for Writers?

Research papers provide a backbone for your articles and support for your thoughts and opinions. Researched articles also provide evergreen material. My article Gender Expectations of the Edo Period still trends despite its age. Although after a point, you may want to consider writing a new, updated version when new data appears.

As a writer, reading research papers gives you more depth to your thinking. While the information may not be directly useful for your articles, the practice of parsing and deep thinking enhances your writing. It forces you to write more clearly. However, you have to be careful not to absorb academic writing’s terrible habits. Business and academic writing provide the best examples of how not to write. Business and academic writing targets specialists who understand the jargon. Likewise, both lean heavily on passive sentence construction, which, while useful, violates good writing principles. Combined with all the data, this poor writing makes research and business papers difficult to read. Why do business and academic writers do this? Passive structure downplays the writer. For academics, this aims to put the study front and center. In business, it allows people to legally squirm out of situations. Either way, indirect writing is poor writing.

For example, when I read a sentence like the following, I parse it into a better sentence as I read it: “This opportunity to research a group of corporate entities’s alpha and beta provides an opportunity to examine the differentials obfuscated by marketing materials, press releases, and earnings calls.” Translation: “Stock data provides accurate data about the company.”

As a writer, being able to translation garbage academic and business writing into useful, readable facts matters. It’s a service that readers value. It takes practice to parse and understand research papers. Fortunately, most research papers provide landmarks as we’ve discussed to help you understand them. Look for the big ideas of the paper instead of getting lost in the data. When you need to include data for your readers, break the data down to its essentials, using the big idea as the foundation for the data. Most of the time, the big idea is what readers care about. If they want to learn more, they can follow your citations (and you are citing right?) to read the research for themselves.

In order to be an informed reader and writer, you need to develop the ability to check your cognitive biases and engage with information that challenges your understanding. Good science, good history, and good writing forces us to grow.

Steps to Understand a Research Paper

1. Read the Abstract.

2. Note the “big idea”.

3. Read the Literature section.

4. Note the context studies and where the study’s hypothesis fits.

5. Read the Discussion section.

6. How did the study prove or disprove the “big idea”?

7. Read the Conclusion.

8. Can the “big idea”, if proven by the study, be generalized? Sample size and make-up determines this.

9. Look up and repeat these steps with the literature the research paper cites.

References

Blanchflower, David (2021) Is happiness U-shaped everywhere? Age and subjective well-being in 145 countries. Journal of Population Economics, 34, 575-624.