self-conscious - Story 126964 | Emotion Vectors in Gemma4-31B

Mark saw the words “Go Skydiving” and felt a familiar tremor of fear. Liam, his partner, had this incredibly adventurous spirit. Mark was…not. He glanced down at his own comfortable clothes, a stark contrast to Liam's usual active wear. The thought of jumping out of a plane sent a wave of nausea through him.

He pictured Liam, a grin plastered across his face, the wind whipping through his hair. The image made Mark’s stomach clench. He fiddled with the list, hoping to find a more relatable item, something they could do together.

“Learn to Play the Guitar”. He could almost hear his partner’s laugh. They had very different skill sets.

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