He tried to act normal, but the knot in his stomach refused to unravel. At the weekly team meeting, he had to sit directly across from the new hire, Jessica, who was clearly making more than he was, based on the clues offered during a casual conversation.

He found himself overly polite, almost deferential, when answering her questions. His usual quick wit and playful banter were replaced by clipped, hesitant responses. The words seemed to stick in his throat.

Later, he avoided the usual post-meeting discussions, making a hurried excuse to leave. Walking home, he felt the city lights blur into a shimmering, indistinct haze, mirroring his own clouded vision. He quickened his pace, as if trying to outrun an invisible pursuer.

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