- Implement SVD axis stability using Lasso regression on fused embeddings
- Add overtone shift analysis to detect semantic content changes
- Implement semantic drift tracking for motion content over time
- Add party voting analysis with cross-ideological voting patterns
- Generate markdown report with visualizations
- Add comprehensive test suite with 12 passing tests
See reports/drift/report.md for analysis results.
- Add scripts/motion_drift.py: analyzes SVD axis stability, semantic drift,
and cross-ideological voting patterns across annual windows
- Add analysis/motion_drift.py: core analysis functions with Procrustes
alignment fallback using party-based sign consistency
- Add matplotlib dependency for static chart generation
- Add tests/test_motion_drift.py: 12 tests covering all analysis functions
- Report output: markdown with embedded PNG charts
Key findings from real data:
- No axes are fully stable (>0.7) across 2019-2026
- All axes show moderate consistency (0.40-0.47) — stable within periods
but flip between cabinet periods (2019/2022/2026 vs 2023/2024/2025)
- Party voting analysis detects cross-ideological voting patterns