It was the office holiday party, and the awkwardness was palpable. Michael had overheard the conversation about salary, and now found himself in a room full of brightly dressed colleagues, all of them seemingly unaware of the silent turmoil that raged within him. He was at a distinct disadvantage.

He clutched his drink a little too tightly, the ice clinking against the glass. He forced a smile, but it felt stiff and unnatural. He made a beeline for the buffet, filling his plate with food he didn't even want, a subconscious attempt to hide.

He found himself gravitating towards the edges of the room, avoiding eye contact and any sort of personal interaction. The music, usually a source of joy, now felt like a discordant cacophony. He retreated to the parking lot early, the cold night air a welcome relief.

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