Methodology Notes
Outlier Handling and Distribution Cuts
Methodology only, results not yet published.No accuracy number appears here until it is measured on a labelled set with sample size, baseline and limitations.
A methodology note on how outliers and edge cases are handled so public distributions stay useful.
Release record
MN-14 · Statistical hygiene
March 2026
8 min
Reference notes
Core Thesis
Institutional trust strengthens when outliers are treated as part of the field, but not allowed to distort interpretive bands that ordinary readers rely on. distribution cuts are chosen to preserve both truth and usability. and the system avoids hiding interesting extremes while also refusing to let them rewrite the center of the graph..
Method in focus
Outliers are treated as part of the field, but not allowed to distort interpretive bands that ordinary readers rely on. Distribution cuts are chosen to preserve both truth and usability.
Guardrail
The system avoids hiding interesting extremes while also refusing to let them rewrite the center of the graph.
Why it matters
This matters because a public observatory loses credibility quickly if its bands are unstable or misleading.
Evidence Chain
Related pages and tools.
Use the links below to inspect the benchmark, observatory or tool pages that extend the same claim into practice.