Where is the
argument?
A practice space for Stephen Toulmin's six-part argument model. Take a real academic paragraph, map its claim, grounds, warrant, backing, qualifier and rebuttal — then compare with peers.
The six elements
The position you want your audience to take.
The evidence supporting the claim.
The reasoning that links grounds to claim.
Theory or prior work that legitimises the warrant.
How far the claim extends — scope and strength.
Conditions under which the claim might fail.
A fire in Ann's house
Toulmin's own everyday illustration, broken into its six functions. Read the sentences in order — together they form a single, well-formed argument.
- 01Grounds
“Smoke is pouring out of the upstairs windows of Ann's house.”
The observable evidence we are starting from.
- 02Warrant
“Where there is smoke billowing from a house, there is almost always a fire inside.”
The reasoning bridge that lets the evidence support the claim.
- 03Backing
“Fire-service incident reports consistently show that visible smoke from a domestic property indicates active combustion.”
The authority — research, theory, codified experience — behind the warrant.
- 04Qualifier
“So, very probably,”
Signals how strongly the claim is being made.
- 05Claim
“Ann's house is on fire and the fire brigade should be called immediately.”
The position the arguer wants the audience to accept.
- 06Rebuttal
“Unless the smoke is from a bonfire in the garden, or steam from a kettle seen through the window.”
Conditions under which the claim would not hold.
Three practice tracks, same model
The map and sentence drills are available with paragraphs drawn from three different scholarly worlds. Pick the one closest to your own writing — Toulmin's six elements apply identically to all.
Empirical paragraph in political psychology / neuroscience.
Source: de Bruin, D., & FeldmanHall, O. (2025). Politically extreme individuals exhibit similar neural processing despite ideological differences. Journal of Personality and Social Psychology, 129(5), 816–833.
Interpretive paragraph spanning literature, philosophy, and Jewish studies.
Source: Felski, R. (2011). Suspicious Minds. Poetics Today, 32(2), 215–234. https://doi.org/10.1215/03335372-1261208
Empirical paragraph on machine learning systems and evaluation.
Source: Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT '21) (pp. 610–623). ACM.