Klima - cross-fraction topoi

Deploy only Raw keywords WP20 vs WP21

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

Rhetorical pattern	AfD 148 speeches in topic	CDU/CSU 208 speeches in topic	Linke 121 speeches in topic	Grüne 166 speeches in topic	SPD 200 speeches in topic
Apokalyptiktopos Existential climate threat: catastrophe, tipping points, doom.	2.1 n=148	0.2 n=208	9.9 n=121	10.6 n=166	2.1 n=200
Generationengerechtigkeit Duty to future generations, intergenerational fairness.	0.5 n=148	1.6 n=208	1.4 n=121	1.7 n=166	0.4 n=200
Technikoptimismus Faith in technology to solve the climate problem.	3.5 n=148	11.9 n=208	4.1 n=121	6.9 n=166	8.0 n=200
Kostentopos Climate policy too expensive, burden on taxpayers and industry.	16.3 n=148	10.2 n=208	20.8 n=121	12.3 n=166	8.2 n=200
Verzichtstopos Climate action requires sacrifice, giving up comforts.	7.5 n=148	3.7 n=208	1.7 n=121	2.8 n=166	0.8 n=200
Wettbewerbstopos Climate as economic race: green industries, competitiveness.	9.2 n=148	9.9 n=208	7.1 n=121	9.9 n=166	6.3 n=200
Wissenschaftstopos Science, IPCC, evidence, expert consensus.	3.5 n=148	4.7 n=208	4.9 n=121	2.4 n=166	2.6 n=200
Klimaskepsistopos Climate skepticism: denial, doubt, conspiracy claims.	5.5 n=148	2.0 n=208	0.7 n=121	0.2 n=166	0.2 n=200

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.