- rank.py: get_weights(profile) — when the profile reads non-tech (sales/finance/HR/ops/support/…),
tilt the weights to role(0.16)/industry(0.12)/semantic(0.12), drop skill(0.18). Tech weights
unchanged. (The competency-skill-backfill was tried + REVERTED — uniform per-role competencies
added no discrimination and Phase 2's real-cosine f_semantic already supplies the non-tech signal.)
- curate.py: non-tech instruction — role/responsibility fit is the spine; a missing skill list is NOT
a negative; a strong role+industry+responsibility+seniority match is a genuine ~80, not ~65.
- test_contracts.py: allowlist the new keyword-handled non-tech vocab (active boards keyword-fold;
numeric codes deferred since the active feed/recall paths don't use them).
Regression (120 pairs): MAE 18.4 → 16.1 (all from non-tech: sales 17.1→13.0, ops 16.3→11.7), recall
holds 0.92, tech unchanged. 31 tests pass.
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