How the 2 sources on this entity in the platform's archive frame it. Tones are auto-classified by an LLM reading the title + raw-content excerpt. Critical doesn't mean wrong; favourable doesn't mean innocent. The distribution is itself the signal.
For each source, the title + the first ~1500 characters of raw content go to an LLM (cheap call) with a prompt asking it to pick exactly one tone from the canonical five:
The classifier runs on a boot-time backfill (small batches, high-priority entities first). New ingested sources also pass through it. The model name (and run date) is stored per source — a future upgrade can re-classify with a stronger model.
A high critical % means the coverage in this archive is adversarial. It does NOT mean the subject is guilty of anything. A high favourable % means the coverage leans positive — it does NOT mean the subject is benign. The distribution shows the editorial frame; verify against the linked primary sources before citing.
Machine-readable: JSON