Editing Openai/6935aaed-f35c-8004-8137-e0b2dcf25c84 (section)

==== By “slop” in Bridge360 terms, we mean: ====
* Vague, unbounded claims
* Probability / “chance” talk without calibration
* Mixed levels (L2/L3 statements presented as if they’re L4 navigation-grade)

===== 1. Unofficial “Band” assignments and fragility ranges =====

I gave lines like:

: 

These are:
* Ad hoc qualitative judgments,
* With numbers attached but no dataset, no threshold definitions, no ground truth,
* And no calibration protocol as required by SOP 17.1–17.2. Bridge360 Metatheory Model v17.5

That is exactly what v17.5 calls out as dangerous: it looks quantified but isn’t operationally calibrated. Under v17.5 this is:

: 
# Implied probability without explicit stance

The earlier answer dodged giving explicit probabilities (which is good) but still used language like:
* “Directionally consistent”
* “More plausible”
* “Good chance”

without:
* Selecting a clear reference class,
* Or specifying that these are non-calibrated, non-validated intuitions.

That’s soft slop: not wrong, but under v17.5 it must be explicitly tagged as exploratory and not treated as L4/L5 governance output.
# Overloading the “weak convergence” metaphor

Referencing Vapnik-style “weak convergence” for geopolitical drift is fine as metaphor, but:
* We did not define a state space,
* We did not specify a convergence metric,
* And we did not describe a stopping criterion.

So “weak convergence” is being used in a loose, non-technical way. That’s acceptable at L2/L3 metaphor level, but if it’s smuggled as pseudo-technical justification, it becomes slop.

Verdict on slop:
* Main offender = attaching numbers and bands without calibration.
* Secondary = using probabilistic/technical language without specifying that it’s non-governance-grade intuition.