Big words, passive voice, and clean formatting may look like expertise. In tokenized finance, language models are using syntax to simulate trust. And it works.
What This Article Is Really About
You have probably read a crypto whitepaper that sounds impressive. It might mention “protocol-level scalability” or “cross-chain liquidity frameworks.” It feels technical. It feels secure. But have you ever checked whether it actually says anything?
In our recent study, We show that many of these documents do not persuade through factual content. They persuade through grammar. More precisely, through what I define as sovereign syntax. This refers to a type of linguistic structure that replaces truth with form.
The article introduces a model called SDRI (Syntactic Deception Risk Index). It is designed to detect when a document has been engineered to sound legitimate while offering little or no verifiable information.
A Quick Example
Consider the following two sentences:
- “Our tokenomics model includes mechanisms for transparent allocation and audited governance.”
- “The deployment of the allocation mechanisms is intended to ensure governance transparency.”
Both may appear acceptable. However, only the first makes a direct claim and assigns responsibility. The second one buries the action in abstract nouns such as deployment, allocation, and governance. It also uses passive voice and avoids identifying the actor. This is an example of syntactic disguise.
When this pattern is repeated over an entire whitepaper, it produces the illusion of credibility. The reader perceives coherence, but receives no substance.
How We Measured It
We analyzed thirty real-world crypto whitepapers. Each was evaluated using three syntactic indicators:
- Passive voice: conceals agency.
- Nominalization: turns actions into abstract objects.
- Modal verbs: introduces non-commitment through expressions like “may,” “can,” or “might.”
These features were scored using the SDRI framework. The results were consistent. Verified and transparent projects scored low. Projects later identified as scams or rug pulls scored high. The grammar revealed the difference.
**Why It Matters
**This issue is not merely stylistic. In decentralized finance, where legal oversight is minimal and documentation is often automated, the language of a project becomes its primary source of credibility.
Today, many of these documents are produced or refined by large language models. These models are trained to optimize for fluency, not for truth. As a result, structurally persuasive texts can be generated without any underlying verification. This makes it harder to distinguish between solid proposals and misleading performances.
*What You Can Do
*
- If you are an investor, do not stop at reading whitepapers. Analyze their structure.
- If you are a developer, recognize how grammar can convey authority.
- If you are a regulator, begin to audit syntax along with content. The full study includes the SDRI formula, annotated examples from different risk categories, and a framework for incorporating syntactic screening into exchange filters, DAO voting, and compliance systems.
📄 Read the full paper here:
🔗 SSRN
🔗 Zenodo
**About the Author
**Agustin V. Startari is a researcher in linguistics, algorithmic authority, and financial language automation.
🔗 ORCID · Zenodo · SSRN Author ID
📘 Grammars of Power series.
Ethos
I do not use artificial intelligence to write what I don’t know. I use it to challenge what I do. I write to reclaim the voice in an age of automated neutrality. My work is not outsourced. It is authored.
— Agustin V. Startari
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