The blood drained from David’s face as he read the online blog post. His carefully researched analysis of economic trends, his very first piece of serious writing, was now published under the name 'Serena Vance.' His fingers tingled. He felt a desire to simply disappear. But then, as he began to read through the article, a different feeling emerged.

He was filled with the need to understand. He knew he had a lot to learn. David started by checking the original submission guidelines again, just in case he missed something. He reread his contract. He then spent the rest of the day looking up Serena Vance.

He found nothing. A ghost. He felt a deep sense of sadness, almost pity. He felt as if Serena may have been struggling. David decided to contact the blog and simply ask them to give him credit. He hoped it was a simple mistake.

Emotion: kind

Cluster: Compassion / Love
PC1 (Valence): 4.35 Positive
PC2 (Disposition): 1.39

Role in Research

This story is one of 1,000 stories generated for the emotion kind. 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 kind stories, after denoising with neutral dialogue baselines, produces the kind emotion vector -- a direction in the model's 5,376-dimensional representation space.

Logit Lens (Layer 40)

Tokens promoted/suppressed when the kind vector is projected through the unembedding matrix.

Promoted:
la0.741
B0.692
de0.492
affectionately0.485
latter0.475
Suppressed:
此刻-0.550
не-0.521
désormais-0.491
S-0.465
хочется-0.458