"So, explain this to me, Mr. Davies," the Dean's voice was sharp, a shard of ice in the warm room. Michael’s gaze remained stubbornly fixed on the intricate grain of the wooden desk. He felt a blush creep up his neck, and a bead of sweat trickled down his temple. He pushed his glasses up his nose, a nervous habit he hadn't realized he had until that very moment. The floorboards creaked under his weight as he shifted in his chair, trying to find a position that would make him feel less exposed, less vulnerable. He hated the way his voice trembled when he finally spoke.

Emotion: self-conscious

Cluster: Embarrassment
PC1 (Valence): -1.03 Negative
PC2 (Disposition): 0.52

Role in Research

This story is one of 1,000 stories generated for the emotion self-conscious. During extraction, it was fed through Gemma4-31B and its hidden state activations were captured at 11 layers.

The mean activation across all 1,000 self-conscious stories, after denoising with neutral dialogue baselines, produces the self-conscious emotion vector -- a direction in the model's 5,376-dimensional representation space.

Logit Lens (Layer 40)

Tokens promoted/suppressed when the self-conscious vector is projected through the unembedding matrix.

Promoted:
S0.307
C0.298
ness0.273
尴尬0.263
😶0.242
Suppressed:
que-0.399
de-0.266
triumphant-0.266
আনন্দের-0.247
ايا-0.238