self-conscious - Story 126156 | Emotion Vectors in Gemma4-31B

“Did you, uh… did you enjoy the interview, too, Liam?” Marcus asked, his voice barely above a whisper. He’d bumped into his friend on the way out, and now they stood awkwardly together in the parking lot.

Liam smiled, a casual, almost dismissive expression. “Yeah, it went well. They seemed impressed.” His tone was light, but his body language exuded complete assurance. Marcus found his own shoulders hunching slightly.

He scuffed his shoe against the pavement. He couldn't shake the feeling that he hadn't presented himself as well. The silence between them grew heavy, filled with unspoken comparisons.

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:

`S`	0.307
`C`	0.298
`ness`	0.273
`尴尬`	0.263
`😶`	0.242

Suppressed:

`que`	-0.399
`de`	-0.266
`triumphant`	-0.266
`আনন্দের`	-0.247
`ايا`	-0.238