Files
motief/reports/overton_window
sgeboers 19e8d5b8ba feat(overton): add category domain decomposition with interactive charts and TDD tests
Populated the right_wing_motions.category column (previously 100% NULL across
3,030 motions) via parallel subagent classification — 80 agents derived a
10-category taxonomy and classified all motions in minutes.

Adds to the Overton QMD report:
- Plotly dropdown filter on Chart 1 to toggle between policy categories
- Chart 7: category delta bar chart (pre/post centrist support per domain)
- Chart 8: quarterly domain trajectories for the 5 largest categories
- Domain Decomposition narrative section

Also fixes a Streamlit tab crash (m.text -> m.body_text) and adds TDD tests.
2026-06-15 21:49:37 +02:00
..

Overton Window Analysis — Reading Guide

This directory contains the complete Overton window analysis: a quantitative investigation into whether the Dutch parliamentary center shifted rightward between 2016 and 2026.

Verdict: The Overton window widened: more right-wing positions became politically acceptable after 2024. Right-wing parties moderated toward it. The shift may be temporary.

Where to Start

  1. Interactive Article — The narrative spine. 9 sections with interactive Plotly charts telling the story from question to answer. Render with quarto render overton_window.qmd.

  2. Synthesis Report — The detailed synthesis of all indicators, uncertainty hierarchy, and the "acceptance through moderation" verdict.

  3. HTML Dashboard — Standalone visual report with gravity-controlled charts, 2D extremity heatmap, and three example motions.

Live Exploration

Explore the data interactively in the Stemwijzer Explorer (uv run streamlit run Home.py):

  • Overton tab — Centrist support trends, right-wing motion browser, summary statistics
  • Kompas tab — SVD party positions (the axes behind the spatial divergence finding)
  • Trajectories tab — Party drift over time (with 2024 breakpoint annotation)
  • SVD Components tab — Which motions drive each ideological axis

Appendix Reports

Each report covers one analytical dimension:

Report What it answers
Breakpoint Analysis When did centrist support surge? How much?
Temporal Trajectory Quarterly resolution — was it gradual or sudden?
Causal Timing Electoral jump vs coalition-driven?
SVD Drift Did party positions converge or diverge?
2D Extremity Temporal Did motion content become more extreme?
2D Correlation Are style and substance independent? (r=0.43)
Party Differentiation Which right-wing party drove the shift? (JA21)
Left-Wing Response Did left parties harden opposition?
Mechanism Classification How do right-wing motions gain centrist support?
Mechanism Validation Inter-rater reliability (κ=0.41)
Voting Margin Continuous margin vs binary pass/fail
Success Correlation Do high-CS motions actually pass more?
Predictive Model Can we predict centrist support? (AUC=0.81)

Methodology

Reproducibility

Regenerate all reports with:

uv run python analysis/right_wing/build_all_reports.py --skip-llm

Status

See STATUS.md for the complete analysis status, data sources, and canonical numbers.