Linguistic argumentation¶
📘 ENGLISH LINGUISTIC RESOURCES FOR ARGUMENTATION
Resource |
Function |
Enables |
Example |
|---|---|---|---|
Discourse Marking System |
Signals logical relations between sentences or clauses |
Inference, Counterargument, Reframing |
The results are consistent. Therefore the model is robust. |
Clause Linking System |
Connects clauses via causal, concessive, or conditional relations |
Inference, Qualification, Counterargument |
Although the method is efficient it introduces risks. |
Modal System (Epistemic Modality) |
Expresses certainty, probability, and epistemic stance |
Inference, Qualification, Evaluation |
The system may perform better under constrained conditions. |
Evidential & Reporting System |
Marks source or attribution of information |
Evidence Attribution, Inference |
According to the report efficiency increased significantly. |
Nominalization System |
Converts processes into abstract entities for reasoning |
Definition, Decomposition, Distinction, Generalization |
The causation of the failure remains unclear. |
Comparative & Scalar System |
Encodes degree and relative evaluation |
Evaluation, Generalization, Distinction |
The new method is significantly more efficient than the baseline. |
Information Structure System |
Controls focus, contrast, and framing within clauses |
Reframing, Distinction, Evaluation |
It is not cost but scalability that matters most. |
Genericity & Quantification System |
Encodes generality and frequency across categories |
Generalization, Inference |
Most users adapt quickly to the system. |
Clause Packaging System (Embedding & Attribution) |
Embeds propositions for stance, distance, or impersonal framing |
Evidence Attribution, Qualification, Inference |
It appears that the system stabilizes over time. |
1. Discourse Marking System¶
Function
Signals logical relations between propositions across sentences.
Core markers
therefore, thus, hence, consequently, however, nevertheless, on the other hand, as a result
Canonical examples
The dataset shows consistent improvement across all conditions. Therefore the method appears robust.
The initial hypothesis was plausible. However the new evidence contradicts it.
Enables
Inference, Counterargument & Concession, Reframing
Nature
Discourse adverbials encoding coherence relations between clauses and sentences.
2. Clause Linking System¶
Function
Connects clauses through causal, concessive, or conditional relations.
Core markers
because, since, so, although, even though, while, if…then
Canonical examples
The model failed because the input data was incomplete.
Although the approach is efficient it introduces new risks.
Enables
Inference, Qualification, Counterargument & Concession
Nature
Subordination system encoding logical relations between clauses.
3. Modal System (Epistemic Modality)¶
Function
Expresses certainty, probability, necessity, and epistemic stance.
Core markers
may, might, must, should, could, likely, probably, appears to, seems to
Canonical examples
The system may perform better under constrained conditions.
This result must be interpreted cautiously given the sample size.
Enables
Inference, Qualification, Evaluation
Nature
Auxiliary and lexical system expressing degrees of epistemic commitment.
4. Evidential & Reporting System¶
Function
Marks the source of information or attribution of claims.
Core markers
according to X, X argues that, X suggests that, X reports that, X claims that, it is reported that, there is evidence that
Canonical examples
According to the report efficiency increased by 15 percent.
Researchers suggest that the effect is context-dependent.
Enables
Evidence Attribution, Inference
Nature
Reporting verbs and evidential constructions encoding epistemic source.
5. Nominalization System¶
Function
Converts processes and relations into abstract entities for reasoning.
Core markers
causation, efficiency, implementation, legitimacy, interaction, development
Canonical examples
The causation of the failure remains unclear.
Efficiency depends on system architecture.
Enables
Definition, Analytical Decomposition, Distinction, Generalization
Nature
Lexical-grammatical abstraction mechanism in academic English.
6. Comparative & Scalar System¶
Function
Encodes degree, ranking, and relative evaluation.
Core markers
more, less, better, worse, significantly, slightly, compared to, relative to
Canonical examples
The new approach is significantly more efficient than the previous one.
Performance is better compared to baseline models.
Enables
Evaluation, Generalization, Distinction (partial)
Nature
Scalar gradability system in adjectives and adverbs.
7. Information Structure System¶
Function
Controls focus, contrast, and framing of information within clauses.
Core markers
it is not X but Y, what matters is…, the real issue is…, it is X that…, topicalization structures
Canonical examples
It is not cost but scalability that determines feasibility.
What matters is the long-term stability of the system.
Enables
Reframing, Distinction, Evaluation
Nature
Focus and prominence management in clause structure.
8. Genericity & Quantification System¶
Function
Expresses generalizations and category-level statements.
Core markers
most, many, some, few, usually, often, typically, in general, as a rule, tends to, is associated with
Canonical examples
Most users adapt quickly to the new system.
In general students perform better with consistent practice.
Enables
Generalization, Inference (statistical form)
Nature
Determiner system + adverbs of frequency + generic reference.
9. Clause Packaging System (Attribution & Embedding)¶
Function
Embeds propositions to signal stance, distance, or impersonal framing.
Core markers
it is said that, it appears that, it is believed that, X suggests that, there is evidence that
Canonical examples
It appears that the system stabilizes after repeated use.
It is believed that early intervention improves outcomes.
Enables
Evidence Attribution, Qualification, Inference
Nature
Impersonal clause constructions and embedding structures.
10. Summary Mapping Logic¶
Each reasoning pattern in Sheet 1 emerges from combinations of these systems, not from a single marker.
Examples:
Inference
→ discourse markers + clause linking + modality + evidential verbs
Reframing
→ information structure + discourse markers
Counterargument
→ concessive linking + discourse markers + evidential reporting
Evaluation
→ scalar system + modal system + evaluative adjectives
Note
This sheet describes the linguistic substrate of argumentative English:
not what writers do, but what English makes structurally easy to express.