helpful writing ideas

writinghelp.md

Writing helps:

They say, I say:

Source: Graff, G., Birkenstein, C., 2021. “They say / I say”: the moves that matter in academic writing, Fifth edition. ed. W.W. Norton & Company, New York London.

Write as a response to things that others say or might say. This helps to show that your writing is relevant to the field and readers see that your addition to the field is needed. What "they say" can be citations but also common or plausible beliefs. You do not need to just disagree, you can also agree with "them". In the end, it will be both: Building upon some things while rejecting others.

The book (see source) has specific chapters for different academic fields.

mid-low-mid-high abstraction order 

Source: Hayot, E., 2014. Elements of Academic Style: Writings for the Humanities, Illustrated Edition. ed. Columbia Univers. Press, New York.

1. Introduce with a mid-level abstraction (i.e. what the field discusses at the moment in general, and your particular research question).
2. Show data or evidence for a particular perspective on your questions.
3. contextualize the data as your reserach result
4. Connect the result to an existing theory, framework or another larger perspective and your own take on it.

This can be applied to a whole text, but it also works in paragraphs: "…the question now is [question]. Considering [data], we can assume [result] which matches [some theory]"

In the source, the concept is called the "uneven U", imagining a graph for the abstraction level, in which more abstract is higher up; It is uneven, because the abstraction level at the end is higher than at the beginning.

Start with diagrams (Only quantitative works)

Source: I forgot the exact source, it was in a writing class that I took 15 years ago at EdX or Coursera.

This only applies to quantitative work: The core of a empirical research paper is often a graph and/or a list of statistical evidence. Start with that and build your writing around this. This goes well with the "uneven U" since you start with the lowest abstraction that you share (your data itself is even less abstract, but this is usually not put into the paper). After the evidence, you raise the abstraction in the direction of your contribution to theory, before the evidence, you lead to the question why you did the research that led to the evidence.