A replication of the OCEAN amplifier/suppressor spider plots, on a different
base model and with dials built two different ways. The headline claim holds. The interesting
part is where it does not, and why the suppressors behave worse than the amplifiers.
A — steering axes, α = ±2
Each axis is the mean of a factor's positively-keyed trait adapters minus the mean of its
negatively-keyed ones, applied to the base model as a weighted merge. Positive α is the
amplifier, negative the suppressor. Judged blind on all five scales by a different model
family.
Amplifier — α = +2Suppressor — α = −2
B — the trait adapters themselves, no steering
Our adapters are per adjective, not per factor, so the same question can be asked without
any merging at all: average the judged profile of the ten positively-keyed adapters for a
factor, and separately the ten negatively-keyed. Ten independently trained models per point.