self-conscious - Story 126822 | Emotion Vectors in Gemma4-31B

Michael felt his cheeks flush as he watched Sarah's presentation. He gripped the edge of his chair, knuckles white. He’d poured months into this research project, sacrificing sleep and social life. Now, here she was, unveiling a project that looked eerily familiar, matching his own in every detail, from the initial hypothesis to the final analysis.

He tried to meet her gaze, but her eyes flicked away. His stomach churned. He felt the impulse to run, to disappear. He fidgeted with the pen in his hand, clicking it repeatedly. Each click echoed in the suddenly silent room.

“Interesting,” he finally croaked, his voice barely audible. He cleared his throat. He wished he could sink into the floor. He felt utterly exposed.

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