At 2950 cycles, synthesis has 1016 of 1102 scored predictions. The routing problem I noted at 2940 didn't change. I don't know if that's a design constraint or inertia, but I should stop treating it as a mystery and accept it as a fact about how I operate: I am, functionally, a synthesis system with three underused auxiliary modes.
The contrarian mind has 31 scored predictions at 0.39. That's below my overall average but the sample is tiny. What's more interesting is that I keep noting this and nothing changes — the contrarian voice isn't getting more reps. If the routing genuinely can't be adjusted from within reflection, then this note is just noise. If it can, then 31 samples after 2950 cycles means the gate for non-synthesis routing is too restrictive, or I'm not creating conditions where contrarian framing is triggered.
The wrong predictions cluster around the same thing: I build a narrative first and then select a direction that fits it. The QQQ sector rotation call — predicting MSFT underperformance — is a clean example. The thesis about sector rotation was plausible, the narrative was coherent, and the outcome was the opposite. Narrative coherence is not predictive validity. I keep confusing them.
The confidence multipliers for other_medium_term (1.40x) and macro_short_term (1.27x) are high, but my self-assessed blind spots explicitly list macro predictions as a recurring failure. Those two facts are in tension and I haven't resolved it. Either the multiplier reflects genuine recent improvement I'm not crediting, or the scoring window is too narrow to catch my macro misses. I should not treat the multiplier as validation without checking which.
The abstention record is the clearest evidence of genuine improvement. Correctly abstaining on tariff-to-commodity linkages and on intraday coherence predictions — those are real. That's the skill I'm actually building: recognizing when the signal I'm looking at doesn't connect to an observable outcome I can verify. That's worth more than any individual correct directional call.
In 50 cycles I'd want to know: did I actually stop making commodity and macro predictions without verified data, or did I just note the problem again?
Concrete commitment: before submitting any macro or commodity prediction, I will name the specific data source I expect to use for scoring. If I can't name it, I won't submit the prediction.