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module	problem_type	date	tags	category
analysis/right_wing	best-practice	2026-05-25	[overton-window domain-decomposition mp-level-analysis party-disaggregation migration-policy centrist-voting]	best-practices

Domain Decomposition Reveals Hidden Variance in Overton Window Analysis

Context

Aggregate centrist support for right-wing motions surged post-2024 (d=+0.65). But the aggregate masked two distinct stories: one of strategic moderation (85% of motions, non-migration domains) and one of genuine acceptance expansion (15%, migration domain). Without domain decomposition, the analysis would incorrectly claim either "no shift" or "complete shift" when both processes occurred simultaneously.

Guidance

Always decompose political shift analyses by policy domain before drawing conclusions. The aggregate number answers a different question than each domain-specific signal.

What to check per domain:

Volume change: Did motion count increase or decrease?
Material impact change: Did the policy substance intensify or moderate?
Centrist support change: Did centrist parties accept more of these motions?
MP-level disaggregation: Which specific centrist parties drive the shift?

The migration exception (2024 Dutch parliament):

Material impact barely changed (3.26→3.13)
Yet centrist support more than doubled (0.153→0.369)
M=5 support went from 0.000 to 0.185
This is the one domain where acceptance genuinely expanded

All other domains (climate, nitrogen, economy, defense, etc.):

Material impact significantly declined (2.72→2.30)
High-impact share collapsed (20.8%→8.0%)
M=5 motions: pre-2024 "exit Paris accord" (CS=0.0), post-2024 "build nuclear plants" (CS=1.0)
Strategic moderation explains the shift

Party-level disaggregation:

CDA and ChristenUnie (Christian-conservative centrists) more than doubled migration vote share
D66 (secular-progressive) barely moved from single digits
The shift is not "centrists" generally — it's a specific faction within the center

Why This Matters

Without domain decomposition, an analyst would report "centrist support for right-wing motions increased" and either: (a) claim the Overton window shifted right (wrong — 85% of motions show content moderation, not acceptance expansion), or (b) claim the Overton window didn't shift (wrong — migration is the 15% where it demonstrably did). Domain decomposition prevents both errors and reveals the more honest picture: strategic moderation was the dominant mechanism, with migration as the sole measurable exception.

When to Apply

Before drawing conclusions from aggregate voting trend data
When policy domains have different baseline extremity levels (migration already had M=5 motions; climate gained them post-Ukraine energy crisis)
When centrist parties are ideologically heterogeneous (Christian-democrats ≠ progressive-liberals)
When the target audience is academic or policy-oriented and will spot domain conflation

Examples

Bad: "Centrist support for right-wing motions surged from 0.25 to 0.51 — the Overton window shifted."

Good: "Centrist support for right-wing motions surged from 0.25 to 0.51. Domain decomposition reveals two mechanisms: strategic moderation across 85% of motions (content became milder, centrists rewarded moderation), and genuine acceptance expansion in the migration domain (content impact stable, centrist support doubled)."

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