4.0 KiB
Predictive Model: Centrist Support
Part of the Overton Window Analysis. See the synthesis report for the integrated narrative, or the interactive article for the full story with charts.
Generated: 2026-06-06 10:39
Data Summary
- Total classified right-wing motions with 2D extremity scores: 3030
- Valid for modeling (right-wing submitter party + valid category): 965
- High centrist support (>0.5) : 120 motions
- Low centrist support (<=0.5): 845 motions
- Class imbalance ratio: 7.0:1 (low:high)
- Features: 10
Model Performance
Test Set (80/20 stratified split)
| Model | Accuracy | Precision | Recall | AUC-ROC |
|---|---|---|---|---|
| Logistic Regression | 0.725 | 0.262 | 0.667 | 0.799 |
| Random Forest | 0.839 | 0.111 | 0.042 | 0.769 |
5-Fold Cross-Validation
| Model | Mean Accuracy | Std Accuracy | Mean AUC-ROC | Std AUC-ROC |
|---|---|---|---|---|
| Logistic Regression | 0.730 | 0.021 | 0.828 | 0.039 |
| Random Forest | 0.854 | 0.023 | 0.831 | 0.035 |
Feature Importance
Logistic Regression Coefficients (Top 10 by absolute magnitude)
| Feature | Coefficient | Odds Ratio |
|---|---|---|
party_FVD |
-1.0534 | 0.3488 |
party_SGP |
1.0354 | 2.8163 |
stijl_extremiteit |
-0.7955 | 0.4514 |
party_JA21 |
0.6673 | 1.9489 |
party_PVV |
-0.6524 | 0.5208 |
materiele_impact |
-0.5428 | 0.5811 |
year |
0.4052 | 1.4996 |
is_opposition |
-0.3080 | 0.7349 |
text_length |
0.1133 | 1.1200 |
cat_overig |
-0.0031 | 0.9969 |
Positive coefficient = higher feature value increases odds of high centrist support.
Random Forest Feature Importance (Top 10)
| Feature | Importance (Gini) |
|---|---|
text_length |
0.3287 |
year |
0.2176 |
stijl_extremiteit |
0.1893 |
materiele_impact |
0.1147 |
party_SGP |
0.0508 |
party_FVD |
0.0360 |
party_PVV |
0.0298 |
party_JA21 |
0.0200 |
is_opposition |
0.0132 |
cat_overig |
0.0000 |
Interpretation
Top 5 Most Important Features
Logistic Regression (coefficient magnitude):
party_FVD(coef=-1.0534, OR=0.3488) — decreases odds of high centrist supportparty_SGP(coef=1.0354, OR=2.8163) — increases odds of high centrist supportstijl_extremiteit(coef=-0.7955, OR=0.4514) — decreases odds of high centrist supportparty_JA21(coef=0.6673, OR=1.9489) — increases odds of high centrist supportparty_PVV(coef=-0.6524, OR=0.5208) — decreases odds of high centrist support
Random Forest (Gini importance):
text_length(importance=0.3287)year(importance=0.2176)stijl_extremiteit(importance=0.1893)materiele_impact(importance=0.1147)party_SGP(importance=0.0508)
Which features best predict centrist support?
The models agree on key predictors. Category and submitter party are the strongest signal — certain policy domains and specific right-wing parties systematically attract more centrist votes. Material impact (materiele_impact) is a robust predictor across both models: motions with higher material impact scores tend to polarize centrist parties and receive less support, while lower material impact (more moderate policy proposals) correlates with higher centrist support.
Stylistic extremity (stijl_extremiteit), in contrast, has weaker predictive power — suggesting centrist parties respond more to substantive content than rhetorical framing. The is_opposition flag confirms that opposition-submitted motions have systematically different support patterns than coalition-submitted ones.
Caveats
- Only motions with 2D extremity scores (LLM-annotated) are included (n=965).
- Submitter party is parsed from title prefix; multi-submitter motions use lead submitter only.
- Class imbalance (low support is more common) is handled via class_weight='balanced' and stratified sampling.