self-conscious - Story 126703 | Emotion Vectors in Gemma4-31B

The moment David heard the name, "Camp Greenleaf," a wave of heat washed over him. He was sure everyone in the meeting room was staring at him. He could feel it in the way his ears were burning. He’d hated that camp.

“Camp Greenleaf was a blast!” Sarah, the office manager, exclaimed. “Anyone else go there?”

David stared intensely at the presentation slides, as if they held the secrets of the universe. He was suddenly fascinated by the graphs. He hadn't expected to run into someone from there.

“Yeah,” he mumbled, trying to keep his voice flat. He felt his hands begin to sweat, and he surreptitiously wiped them on his trousers.

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