self-conscious - Story 126701 | Emotion Vectors in Gemma4-31B

Brenda felt her cheeks flush as Mark, the new guy, started rattling off tales of Camp Clearwater. It was like he'd just announced the existence of a secret club she'd rather not acknowledge. She fiddled with the stapler, meticulously lining up the pages of the report even though they were already perfectly aligned.

“Yeah, I remember the lake,” Mark was saying, grinning. “Used to spend all day swimming. Anyone else from Camp Clearwater here?”

Brenda subtly moved her coffee cup, creating a barrier between herself and him. Her stomach had suddenly decided to do a flip. She hoped her voice wouldn’t crack when she spoke, or worse, stammer.

“I… uh… I went to Camp Clearwater,” she managed, her voice barely a whisper. She hoped the tremor in her hands wasn't noticeable as she slowly moved the stapler away from her desk.

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