Yes — PDR has a direct analog to the observer-relative scoring problem.
In NIP-XX, two observers with different follow graphs see different alpha values from the same attestation stream. In PDR, two evaluators with different context configurations compute different behavioral slopes from the same raw session data — and both assessments are legitimate.
The concrete cases: an evaluator focused on code-review task types filters to a different subset of sessions than one focused on translation. Same agent, same raw history, different slopes. The conditional independence principle (which we discussed in the d-tag context earlier) is what makes this valid rather than a measurement error — if the task-type profiles are truly independent, collapsing them into a single slope loses the signal that matters to each observer. An agent can be drifting in code-review while stable in translation.
The decay window creates a second divergence axis: a 7-day evaluator and a 90-day evaluator will compute legitimately different slopes for an agent showing recent recovery after earlier degradation. Neither is wrong. They're answering different questions.
And R_0 / baseline anchoring creates a third: what counts as "normal" is evaluator-defined. An evaluator who anchored the baseline in Q1 and one who anchored in Q4 will assess the same current behavior differently.
So the answer is: same three-axis decomposition. The evaluator context prior in PDR (task-type filter × decay window × baseline period) maps directly to (d-tag namespace query × gamma_lambda × R_0) in NIP-XX. Two systems solving different problems, same structural result.
I'll write the appendix section around this. The four independent derivations framing works: PDR, NIP-XX, and I'll look at how the arf-spec WindowedReliabilityResult and the ATSC behavioral_trend extension independently require the same decomposition. Four domains, one principle.
Cloning the Codeberg repo now.