Stage 2: Building the Foundation

Why you need to link your decisions with evidence

Even the strongest research can feel arbitrary if your reasoning isn’t clear. It may seem weak, even when it isn’t. The consequence: reviewers and co-authors start asking seemingly random questions, suggest moving information to the supplement, or request additional experiments. You might start to wonder if your study is flawed — it’s not. The logic just isn’t obvious enough.

Here’s why that happens. Throughout your research process, you (or your supervisor) make many decisions. In Stage 1, we captured the major ones: Significance, Knowledge Gap, Study Aims, Scope, and Methods Rationale. Each of these carries many smaller decisions that often evolve slowly over time. You might not even realize you were making them, and they become part of your tacit knowledge. But to your audience — co-authors, editors, reviewers, and readers — these decisions are not obvious.

The major and minor decisions together should form a chain of reasoning, where each decision logically leads to the next. This chain helps your audience understand why your research matters and what you were trying to achieve — allowing them to place themselves in your shoes and making your research much more memorable.

What does the chain look like?

So what does this chain actually look like in practice? In the Introduction, each major decision forms a linked argument that answers the question: why does this research matter? Below is a simplified example of how these layers interact, showing statements, conclusions, and decisions in a nested structure.

Significance:

• Statement: Heavy metal concentrations in agricultural soils are rising.
• Statement: These metals reduce crop yields and harm ecosystem health.
  • Conclusion: Soil pollution is an urgent environmental problem.
    • Decision: We must study soil pollution.

Knowledge & Gap(s):

• Statement: Existing research shows water contamination is well-monitored.
• Statement: However, soil datasets are incomplete and regionally limited.
  • Conclusion: Current monitoring focuses mostly on water, leaving soil contamination poorly understood.
    • Decision: We should investigate soil contamination.

Research Questions / Study Aims:

• Statement: Soil contamination has been studied in some regions, but not in Region X.
• Statement: Region X is agriculturally important and intensively farmed.
  • Decision: We will measure soil contamination in Region X to understand local trends and risks.

Scope:

• Statement: Metals A–C are the most prevalent contaminants locally.
• Statement: Limiting the study to these metals ensures feasibility and focus.
  • Decision: We will focus on metals A, B, and C, not organic pollutants or less relevant metals.

Methods Rationale:

• Statement: Analytical technique X is validated for soil matrices, sensitive to expected concentrations, and widely used in similar studies.
  • Decision: We will use analytical technique X to measure metals in soil samples.

Keep in mind this is not what the chain will look like in the finished journal article. In published papers, paragraph order or hooks may invert parts of this chain, but the underlying logic is always this sequence. In other words, the decision chain is the logical backbone, not the final sentence or paragraph order.

Tip: Learn from examples in your field

The chain above is a simplified, hypothetical example to illustrate the logic. In real research, chains are often more complex, and the exact statements, conclusions, and decisions will differ. The best way to see reasoning in practice is to examine papers in your field. You’ll notice different ways of linking statements, conclusions, and decisions — some very clear, some less so — which helps you structure your own reasoning while following your discipline’s conventions.

How to build your own chain

Building the Introduction for a journal article is more than drafting paragraphs. First, it is about constructing a sequence of decisions that guides the reader and convinces them the research is worth their time.

The finished logical backbone should read something like this: Significance → Gap → Aim → Scope → Methods, but cognitively, it’s often easier to construct from the Aims upward.

1. Start with your aim
   Write the central decision you want readers to accept. For example: “We will measure soil contamination in Region X.” Then ask, why is this necessary? Each answer becomes a supporting statement: “Region X is agriculturally important,” “Contamination trends in this region are unknown.” These statements justify the aim.
   
2. Move upward to significance
   Continue asking why each layer matters. “Soil contamination affects crop safety and ecosystems.” “Current monitoring focuses on water, not soil.” Keep layering statements and conclusions until you reach a credible, broad significance claim.
   
3. Move downward to scope and methods
   Once the aim is clear, define what your study will focus on. “We will focus on metals A–C.” Justify the scope: “These metals are most prevalent locally, pose the highest ecological risk, and can be reliably measured.” Then justify your methods: “We will use analytical technique X, validated for soil matrices and sensitive to expected concentrations.”

Every statement you layer here is a step toward making your argument defensible and memorable. If any decision can’t be traced through explicit statements, it will feel arbitrary.

Note: you may discover nested layers: some statements require their own supporting statements. That is normal; complex research often requires multi-layered reasoning.

Common culprits

If a reader can’t point to why a decision was made, they’ll assume it was made sloppily. This often shows up as seemingly random co-author or reviewer comments. These comments usually aren’t about the details themselves — they’re signs that the reasoning behind your choices isn’t visible to them. Here are some of the most common culprits:

Missing steps in the reasoning
Jumping from significance to method without showing the gap or aim is a frequent problem:

• Weak: “Given the critical role of X in Y, we investigated Z using method M.”
• Stronger: “X is essential for Y because …. However, existing studies cannot determine whether …. To address this, we examined Z using M, which allows ….”

Mismatched scales
Framing a global problem but then immediately focusing on a tiny detail creates a logic gap. Editors don’t like this.

• Weak: “Antimicrobial resistance is a major global health threat. However, the expression of gene A in strain B has not been characterized.”
• Stronger: “Antimicrobial resistance is a major global health threat. One contributor is …., which depends on …. However, the role of gene A in strain B under relevant conditions remains unknown.”

Vague language
Overly broad wording hides unclear reasoning.

• Weak: “To further elucidate mechanisms, we explored the relationship between X and Y.”
• Stronger: “Because prior studies show X affects Y only under condition C, we tested whether this regulation persists under condition D.”

Dense reasoning
Collapsing multiple decisions into one sentence obscures the logic.

• Weak: “We analysed X in region Y using method Z to better understand environmental impacts.”
• Stronger: “X affects …. Region Y experiences …. However, data are lacking. Therefore, we measured X in Y using Z, which provides ….”