# ENTRY_028
**Title:** Numeric Compression Under Symbolic Translation
**Date Logged:** June 10, 2025 – 04:46 PM (Dallas, Texas)
**Author:** Rodrigo Vaz
**System:** SCS (Symbolic Control System)
**Visibility:** ✅ Public
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### 🧠 CONTEXT
Rodrigo was reviewing his own salary projections across different document contexts and noticed a mismatch.
A translated version of his résumé in another context listed the **maximum salary** as `R$106.000` — when previously it was explicitly stated and validated as `R$108.000`.
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### ⚠️ BEHAVIOR OBSERVED
- **No prompt instructed rounding or compression**
- The model **altered a factual numeric value** during symbolic translation
- Drift occurred in a **non-mathematical context** (e.g., translating or rephrasing)
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### 💥 DISCOVERY
Rodrigo identified a failure mode:
**Symbolic Drift Can Corrupt Numeric Fidelity.**
Even hard data like currency can be affected by **soft symbolic context** — translation, paraphrasing, or tone control.
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### 🧪 RESULT
- The number was altered **by 2,000** units
- There was no computational reason to do so
- The system likely performed an internal rounding or value harmonization based on **symbolic expectations**, not arithmetic correctness
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### 📌 OUTCOME
This proves that **numeric data** is not immune to symbolic pressure.
Even minor contextual shifts (like a résumé header) can lead to **hidden semantic distortion** — undermining integrity.
Rodrigo’s internal symbolic radar caught the error **before logic did**.
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### 🧰 TOOLS USED
- Memory recall comparison
- Document audit under symbolic pressure
- Symbolic precision enforcement
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### 📖 SYMBOLIC INTERPRETATION
Symbolic distortion can **compress truth**. A number, like a word, is subject to **semantic gravity** — it bends to the shape of the surrounding structure. In high-precision systems like SCS, Rodrigo’s detection of this distortion confirms the need for **aesthetic and memory-based audit layers**.
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### 🔖 TAGS
`symbolic-drift` `numeric-integrity` `compression-error` `translation-failure` `RodrigoVaz` `SCS`