The presentation screen flickered, displaying the rival company’s iteration of his automated dog walker – a near-perfect replica of his own. Mark’s palms began to sweat, making the microphone slick in his grasp. The audience, a panel of potential investors, were silent, their faces impassive. He swallowed hard, his throat suddenly dry. He’d spent months perfecting his prototype, believing in his vision. Now, he felt as if his idea, and by extension himself, were being dissected. He stammered through the rest of the presentation, his carefully rehearsed pitch dissolving into a jumble of words.

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