Innere Sicherheit - cross-fraction topoi

Deploy only Raw keywords WP20 vs WP21

Topic filter: speech_topics.topic_label = "Innere Sicherheit". Showing raw keyword density. No stance filtering. Mostly useful as a baseline against the deploy-only view.

Rhetorical pattern	AfD 176 speeches in topic	CDU/CSU 183 speeches in topic	Linke 97 speeches in topic	Grüne 129 speeches in topic	SPD 143 speeches in topic
Härtetopos Tougher penalties, harsher sentences, zero tolerance.	6.6 n=176	7.2 n=183	6.2 n=97	4.0 n=129	5.7 n=143
Rechtsdurchsetzungstopos Enforce existing law: deport, prosecute, no leniency.	50.9 n=176	57.5 n=183	45.3 n=97	43.9 n=129	55.9 n=143
Polizeistärkungstopos More police, better equipment, more powers.	49.6 n=176	32.6 n=183	27.2 n=97	26.7 n=129	48.9 n=143
Bürgerrechtstopos Civil liberties, privacy, pushback on surveillance.	11.1 n=176	7.8 n=183	17.0 n=97	8.9 n=129	8.0 n=143
Extremismustopos Extremism: right-wing, left-wing, Islamist threat framing.	28.0 n=176	18.3 n=183	29.1 n=97	51.2 n=129	21.0 n=143
Präventionstopos Prevention: education, social work, deradicalisation.	3.2 n=176	3.1 n=183	9.2 n=97	6.7 n=129	6.9 n=143
Bedrohungslagetopos Threat assessment: threat level, intelligence reporting.	5.5 n=176	2.5 n=183	1.8 n=97	4.2 n=129	3.7 n=143
Vertrauenstopos Trust in institutions, police, judiciary.	4.5 n=176	4.7 n=183	2.2 n=97	3.6 n=129	6.4 n=143

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.