self-conscious - Story 126153 | Emotion Vectors in Gemma4-31B

The waiting room seemed to shrink with every passing minute. Sarah kept replaying the interview in her head, analyzing every word, every gesture. Had she sounded too eager? Not eager enough? She chewed on her thumbnail, the sharp taste metallic.

Liam's confident strides as he walked out of the interview room, gave her a pang. He'd looked pleased with himself. Sarah found her attention drawn to the way he held himself, a sense of ease that she could only dream of achieving.

The floral wallpaper began to look aggressive. The scent of air freshener seemed overwhelming. When her name was finally called, her voice cracked as she followed the secretary to the interview room.

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