Migration - cross-fraction topoi
Topic filter: speech_topics.topic_label = "Migration". Showing raw keyword density. No stance filtering. Mostly useful as a baseline against the deploy-only view.
| Rhetorical pattern | AfD 247 speeches in topic |
CDU/CSU 256 speeches in topic |
Linke 147 speeches in topic |
Grüne 294 speeches in topic |
SPD 241 speeches in topic |
|---|---|---|---|---|---|
|
Gefahrentopos
Migration framed as a security threat. Crime, terror, danger.
|
11.8 n=247 | 6.0 n=256 | 5.9 n=147 | 6.1 n=294 | 4.6 n=241 |
|
Belastungstopos
Migration as a burden on the welfare state, housing, schools.
|
8.4 n=247 | 4.8 n=256 | 4.8 n=147 | 1.9 n=294 | 1.8 n=241 |
|
Nutzentopos
Migration as a benefit: skilled labour, growth, demographics.
|
3.1 n=247 | 2.4 n=256 | 2.6 n=147 | 4.4 n=294 | 4.6 n=241 |
|
Schadentopos
Damage and decline caused by bad migration policy.
|
3.0 n=247 | 1.2 n=256 | 1.7 n=147 | 2.3 n=294 | 1.2 n=241 |
|
Humanitätstopos
Humanitarian duty: asylum, refugees, human dignity.
|
7.4 n=247 | 9.8 n=256 | 13.6 n=147 | 12.4 n=294 | 9.0 n=241 |
|
Kulturtopos
Cultural identity, integration, national values, language.
|
3.5 n=247 | 1.4 n=256 | 2.0 n=147 | 1.3 n=294 | 2.4 n=241 |
|
Rechtsstaatstopos
Rule of law: laws, courts, enforcement, due process.
|
35.3 n=247 | 20.2 n=256 | 10.6 n=147 | 12.7 n=294 | 11.1 n=241 |
|
Mißbrauchstopos
Abuse of the asylum system: bogus claims, fraud.
|
4.4 n=247 | 2.0 n=256 | 0.6 n=147 | 1.5 n=294 | 2.2 n=241 |
|
FlutMetapher
Flood metaphors: wave, stream, mass. Dehumanising scale imagery.
|
2.4 n=247 | 1.4 n=256 | 0.2 n=147 | 0.4 n=294 | 0.1 n=241 |
|
EigenVsFremdgruppe
Us vs them: our people against outsiders or foreigners.
|
5.6 n=247 | 3.8 n=256 | 1.5 n=147 | 2.6 n=294 | 2.5 n=241 |
Cell value: average count of that rhetorical pattern per 10,000 words, computed only over the speeches where the stance pass labelled this pattern as deploy (speaker uses the frame as their own argument). The number under each value (n=X) is how many speeches contributed. Cells with n < 3 are shown as "n=X" without a density value because the average isn't trustworthy at that sample size. The thin bar under each cell shows the stance split across all speeches that triggered this pattern: orange = deploy, blue = critique, grey = unrelated. Click any cell to read the speeches behind it.