self-conscious - Story 126692 | Emotion Vectors in Gemma4-31B

The meeting room felt cold, the air thick with anticipation. David found himself tugging at the collar of his shirt, even though he'd loosened his tie hours ago. He noticed the way Sarah, his rival, was leaning forward, her posture perfect, her expression calm. He shifted uncomfortably in his chair.

His palms were slick. He hadn’t slept well the night before. His thoughts raced, running through every possible scenario, every perceived flaw. He felt a bead of sweat trickle down his temple.

"So," the CEO began, his voice booming. David swallowed, his throat suddenly dry. He found himself avoiding eye contact, focusing on the intricate pattern of the carpet.

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