Soultrace 3.0: The Trait Model 🚀
We just shipped a major overhaul to how Soultrace works under the hood. Version 3.0 replaces our direct color classification with a two-stage latent trait model. Here's what changed and why it matters.
The Old Way (v2.x)
Our previous system updated color probabilities directly from your answers:
Answer → P(color | answer) → Updated color distribution
This worked, but had problems:
- No trait grounding: Colors were computed from raw answer patterns, not established psychological constructs
- Response style bias: Extreme responders (always picking 7) got different results than moderate responders (picking 5), even with identical underlying personalities
- Calibration headache: We needed to tune likelihood tables for every question × color × score combination
The New Way (v3.0)
Now we infer 8 latent psychological traits first, then transform those into colors:
Answer → Trait Updates (Bayesian) → Weight Matrix × Traits → Softmax → Colors
The 8 Traits
| Trait | What It Measures |
|---|---|
| Conscientiousness | Organization, dependability, self-discipline |
| Need for Cognition | Enjoying effortful thinking |
| Analytical Thinking | Preference for systematic reasoning |
| Agency Motivation | Drive for achievement and power |
| Promotion Focus | Orientation toward gains and aspirations |
| Sensation Seeking | Need for novel, intense experiences |
| Emotional Expressivity | Comfort with displaying emotions |
| Communion Motivation | Drive for connection and belonging |
These aren't invented constructs. They come from decades of personality psychology research (Costa & McCrae, Cacioppo & Petty, Higgins, Zuckerman, etc.).
ERS Conditioning
The biggest improvement: Extreme Response Style (ERS) correction.
Some people systematically pick endpoints (1, 7). Others prefer moderate answers (3, 4, 5). This response style is independent of actual personality but naive models conflate them.
We now model ERS as a separate latent variable. The first few answers calibrate your response style, then all subsequent trait updates are conditioned on it. Someone who always picks "strongly agree" gets similar trait estimates to someone who picks "agree."
Smarter Question Selection
Question selection now targets trait uncertainty, not color uncertainty. We pick questions that maximize information gain across the specific traits that are still uncertain, plus a coverage bonus to ensure all 8 traits get measured.
This means faster convergence: stable results in ~24 questions instead of 50+.
What You'll Notice
Honestly? The results page looks the same. You still get a 5-color distribution and an archetype match.
But the underlying estimates are more robust:
- Less sensitive to your response style quirks
- Grounded in established psychological constructs
- Better calibrated (random answers → uniform distribution)
The Math
If you want the full breakdown (Bayesian updates, weight matrices, information gain calculations), check out the technical deep-dive.
Try It
The new model is live now. Take the test and see how it feels.