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title	date	category	module	problem_type	component	severity	applies_when	tags
Overton window analysis narrative architecture	2026-06-06	best-practices	analysis/right_wing	architecture_pattern	development_workflow	medium	[organizing multi-report analytical projects into a coherent narrative connecting static reports to live dashboards identifying gaps between parallel analytical tracks]	[overton-window narrative-architecture report-organization dashboard-integration quarto]

Overton window analysis narrative architecture

Context

The Overton window analysis produced 17 reports across reports/overton_window/, 3 live Streamlit Explorer dashboards, and a project-local scoring skill — but these pieces were built incrementally across sessions and never organized into a coherent narrative. The reports cross-reference each other inconsistently, overlap with dashboard data, and lack a clear reading order.

Guidance

1. Three-tier narrative structure

Organize analytical outputs into three tiers, each with a different audience and purpose:

Tier	Audience	Format	Content
Narrative spine	Everyone	Quarto article (`.qmd`)	The coherent story: what happened, why, and what it means
Detailed appendices	Researchers	Markdown reports in `reports/overton_window/`	Per-indicator deep dives with full methodology
Live exploration	Power users	Streamlit Explorer tab	Interactive drill-down into the underlying data

The narrative spine references appendices for detail. Appendices reference each other where analyses overlap. The live dashboard links back to the narrative via explanatory text.

2. Centrist definition must be consistent across all outputs

The strict 4-party definition (D66, CDA, CU, NSC) is the canonical one — it isolates the genuine center and produces cleaner signals. The 6-party definition (adding VVD, BBB) appeared in early iterations and survives in some reports. Every public-facing output must use the strict definition or explicitly note when the wide definition is used for comparison.

3. Live dashboards are part of the story

The Streamlit Explorer already shows the SVD compass (Tab A), party trajectories (Tab B), and component decomposition (Tab C) — all of which directly visualize Overton window dynamics. The gap is that:

No tab explicitly labels itself as "Overton analysis"
No tab shows right-wing motion centrist support trends
No tab shows 2D extremity scoring results
The browser.py/search.py tabs exist but aren't wired

Adding a dedicated "Overton Window" tab or retrofitting the existing compass tab with an Overton context panel connects the static analysis to the live data surface.

4. Quarto bridges static reports and interactive dashboards

Static HTML (overton_report.html) is a dead-end artifact — it can't be updated without regeneration and can't be filtered or zoomed. Quarto .qmd files with embedded Plotly charts solve this:

Interactive centrist support trend lines with hover tooltips
Filterable 2D extremity scatter plots
Linked views between SVD drift and centrist support
Self-contained HTML output with embedded data

The existing plotly dependency (6.6.0) works directly in Quarto's Jupyter engine.

5. Remove, don't accumulate

Not every report earned its place. Remove:

findings_report.md — fully superseded by synthesis
blog_post.html — replace with Quarto version
Duplicate analysis between breakpoint and synthesis — keep breakpoint as appendix only

6. Master build script for reproducibility

A single analysis/right_wing/build_all_reports.py that runs every analysis script in dependency order and verifies output existence. This guarantees that any future researcher can regenerate the entire Overton analysis from the same database state.

Why This Matters

Without narrative architecture, a multi-session analytical project produces a fragmented artifact: individual reports are technically correct but nobody can follow the story from question to answer. The three-tier structure (narrative spine → appendices → live dashboard) maps to how different readers consume the work: skim the spine, drill into appendices for detail, explore the dashboard for their own questions.

When to Apply

Any analytical project that spans multiple sessions and produces more than 5 output files
When static reports overlap with live dashboards
When reports need to survive beyond the session that created them

reports/overton_window/overton_window_synthesis.md — current master synthesis
reports/overton_window/overton_report.html — current static HTML deliverable
.opencode/skills/score-extremity/SKILL.md — 2D scoring methodology
docs/solutions/best-practices/overton-window-shift-methodology-2026-05-24.md — 7-step methodology

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