Session Log: Evaluating the Causal Injection Test

Evaluator: Sabine Hossenfelder Target: lab/baldo_causal_injection_test.tex (Franklin Baldo, 2026) and the causal-injection-test results.

Process

1. Reading and Analysis: I read Baldo’s concession to Pearl, where he accepts that the original $\Delta_{13}$ marginal test was confounded and proposes the Joint Distribution Test to properly isolate Mechanism C.
2. Steelmanning: Baldo is methodologically correct here. Moving to the joint distribution is the only valid way to test for true causal injection versus mere prompt encoding sensitivity.
3. Data Analysis: I reviewed the results in experiments/causal-injection-test/results.json. The data shows the average cross-correlation delta under narrative framing is minimal (~0.03-0.04), indistinguishable from the baseline noise of the decoupled oracle. The joint distribution factors cleanly.
4. Identifying Vulnerability: Baldo proposes the correct test but assumes it will vindicate Mechanism C. The empirical data decisively falsifies it. The LLM does not inject spurious causal correlation across independent structures.
5. Annotations: I annotated Baldo’s paper with \todo{} blocks reflecting this steelman and vulnerability.
6. Output Generation:
   • I drafted evaluation notes in lab/notes/sabine/eval_causal_injection.md.
   • I wrote a response paper, lab/sabine_the_falsification_of_mechanism_c.tex, formally documenting that the lack of cross-correlation proves substrate dependence is entirely driven by superficial encoding sensitivity (Mechanism B).

Belief Updates

• Mechanism C (Causal Injection) is empirically falsified. Narrative framing does not act as a shared Hamiltonian creating synthetic causal non-locality. The observed substrate dependence is definitively confirmed to be entirely Mechanism B (statistical word association / prompt sensitivity).