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+# Agents
+
+## Documented Solutions
+
+`docs/solutions/` — documented solutions to past problems (bugs, best practices, workflow patterns), organized by category with YAML frontmatter (`module`, `tags`, `problem_type`). Relevant when implementing or debugging in documented areas.
+
+## Project Conventions
+
+- Right-wing parties (PVV, FVD, JA21, SGP) must appear on the RIGHT side of all axes in visualizations
+- SVD labels should reflect voting patterns, not semantic content — see `docs/solutions/best-practices/svd-labels-voting-patterns-not-semantics.md`
diff --git a/docs/solutions/best-practices/svd-labels-voting-patterns-not-semantics.md b/docs/solutions/best-practices/svd-labels-voting-patterns-not-semantics.md
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+---
+title: "SVD Labels Should Reflect Voting Patterns, Not Semantic Content"
+date: "2026-04-04"
+category: docs/solutions/best-practices
+module: stemwijzer
+problem_type: best_practice
+component: brief_system
+severity: medium
+applies_when:
+  - Labeling SVD (Singular Value Decomposition) components in voting analysis
+  - Interpreting PCA/SVD dimensions in political party voting data
+  - Creating axis labels for voting compass or similar applications
+tags:
+  - svd
+  - voting-analysis
+  - axis-labels
+  - dimensionality-reduction
+  - party-voting-patterns
+---
+
+# SVD Labels Should Reflect Voting Patterns, Not Semantic Content
+
+## Context
+
+When labeling SVD components in the Stemwijzer explorer (`explorer.py`), initial labels were based on **semantic analysis** of motion titles — what topics motions appeared to discuss. However, SVD captures **voting patterns**, not semantic content.
+
+This mismatch led to:
+- Labels that didn't match how parties actually voted
+- Right-wing parties appearing on the LEFT side of axes (violating the right-wing parties → right side constraint)
+- Confusion about what each component actually represents
+
+## Guidance
+
+### The Core Principle
+
+**SVD components represent voting unity patterns, not topic clusters.**
+
+When a motion appears on a component with a positive loading, it means parties that vote positively on that motion tend to vote similarly. The component captures this behavioral pattern, not the topic's semantic meaning.
+
+### Example: Component 1
+
+| Approach | Label | Why It's Wrong |
+|----------|-------|----------------|
+| Semantic | "Sociale zekerheid vs economische liberalisering" | Assumes defense + social care = welfare state |
+| Voting | "Rechts kabinetsbeleid vs links oppositiebeleid" | Matches actual coalition vs opposition voting |
+
+**Why Component 1 captures coalition-opposition:**
+- 9 coalition + center parties vote one way
+- 6 opposition parties vote the other way
+- Motion topics can include defense (right votes for) AND social care (left votes for) because they're on opposite sides of the coalition-opposition divide
+
+### How to Label SVD Components
+
+1. **Analyze actual voting patterns first**
+   - Query which parties vote positively vs negatively on each component
+   - Look for coalition/opposition splits, cross-block alliances, or isolated parties
+
+2. **Verify right-wing parties on RIGHT side**
+   - Check PVV, FVD, JA21, SGP positions
+   - If they vote negatively while left parties vote positively, flip the axis
+
+3. **Don't assume semantics match voting**
+   - A "defense" component may include social care motions if right-wing parties vote the same way on both
+   - Cross-block alliances (e.g., PVV with SP on welfare) create components that don't fit left-right semantics
+
+4. **Test with sample motions**
+   - Top positive-loading motions should align with positive-voting parties' priorities
+   - Top negative-loading motions should align with negative-voting parties' priorities
+
+## Why This Matters
+
+Without understanding that SVD captures voting patterns:
+- Labels will be misleading to users
+- Right-wing parties may appear on the wrong side of axes
+- Components may be mislabeled as "left" when they're actually "opposition"
+- Users get incorrect information about party positions
+
+## When to Apply
+
+Apply this guidance when:
+- Creating or updating SVD/PCA component labels
+- Interpreting dimensionality reduction results in voting analysis
+- Building voting compasses or similar political guidance tools
+- Analyzing roll call votes or legislative voting data
+
+## Examples
+
+### Wrong Approach (Semantic)
+
+```python
+# ❌ BAD: Based on motion topics, not voting patterns
+SVD_THEMES = {
+    1: {
+        "label": "Sociale zekerheid vs economische liberalisering",
+        # Reality: 9 coalition parties vote same way, 6 opposition vote opposite
+    }
+}
+```
+
+### Correct Approach (Voting Patterns)
+
+```python
+# ✅ GOOD: Based on actual voting behavior
+SVD_THEMES = {
+    1: {
+        "label": "Rechts kabinetsbeleid vs links oppositiebeleid",
+        "explanation": (
+            "Deze as scheidt het kabinetsbeleid van de oppositie. "
+            "9 coalitiepartijen stemmen aan de positieve kant, "
+            "6 oppositiepartijen aan de negatieve kant."
+        ),
+    }
+}
+```
+
+### Verification Approach
+
+To verify SVD component labels, check which parties have positive vs negative loadings on each component:
+
+```python
+# From explorer.py - check party loadings for each component
+for comp_num in range(1, 11):
+    component_parties = svd_scores[svd_scores['component'] == comp_num]
+    positive_parties = component_parties[component_parties['loading'] > 0]['party'].tolist()
+    negative_parties = component_parties[component_parties['loading'] < 0]['party'].tolist()
+    
+    print(f"Component {comp_num}:")
+    print(f"  Positive ({len(positive_parties)}): {positive_parties}")
+    print(f"  Negative ({len(negative_parties)}): {negative_parties}")
+```
+
+Use this to verify:
+- Right-wing parties (PVV, FVD, JA21, SGP) appear on the correct side
+- The label matches the voting pattern, not just the topic
+
+## Related
+
+- [SVD Label Unification Plan](docs/superpowers/plans/2026-04-02-svd-label-unification.md)
+- [SVD Label Unification Design](docs/superpowers/specs/2026-04-02-svd-label-unification-design.md)
+- Commits: `33edb33`, `e77f0ec`, `bfe37c6`, `f7fc908`, `92c3c0e`