She stared at the magazine, the glossy cover mocking her. Inside, her meticulously researched piece, now credited to “Marcus Thorne.” A knot tightened in her chest. She found herself clutching the magazine so tightly, her knuckles were white. The feeling of… helplessness washed over her.

She had rehearsed this in her mind a hundred times: a polite, assertive email, pointing out the mistake. But as she sat at her desk, her fingers froze on the keyboard. Her mouth felt dry. The thought of causing conflict, of upsetting the established order, filled her with dread.

Later, she found herself making excuses to her friends, avoiding the topic. “Oh, it’s not a big deal,” she’d murmur, her voice barely a whisper. She spent the evening replaying the moment she handed over the manuscript, remembering the editor's curt nod, the way her own voice faltered.

Emotion: dependent

Cluster: Shame / Guilt
PC1 (Valence): -1.05 Negative
PC2 (Disposition): 0.69

Role in Research

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

Logit Lens (Layer 40)

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

Promoted:
de0.489
缺乏0.395
even0.310
either0.301
'0.297
Suppressed:
笑道-0.309
不久-0.293
一脸-0.263
затем-0.263
庆祝-0.258