self-conscious - Story 126273 | Emotion Vectors in Gemma4-31B

The coffee tasted bitter. Sarah grimaced, setting the cup down on her new desk in the IT department. Everything felt unfamiliar, the jargon, the equipment, the complex web of interconnected systems. She missed the predictable routine of the HR department, the simple clarity of personnel files. She missed her old office, a space built over years that she'd grown accustomed to.

She felt a flush creep up her neck as she listened to the IT team's conversation. They spoke in code, their discussions a whirlwind of acronyms and technical terms. When she tried to interject, her voice felt small and uncertain. She quickly retreated, pretending to study her task list, trying to look busy, trying to look like she belonged.

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