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Core Concepts

A short glossary — useful if you're reading this after hearing a talk about the project rather than coming in as an engineer.

  • Target group / identity axis — who the text is about: an ethnic, religious, gender, national-origin, or political group. The engine only ever flags harm against a named group — text with no identifiable target group is never flagged (require_target_present in the taxonomy).
  • Harm mechanism — how the text is harmful. Six are currently implemented: animalization, demonization, objectification, criminalization, direct_call_to_violence, and false_attribution. These map to three broader categories: dehumanization, incitement, and narrative_distortion.
  • Taxonomy — the versioned YAML file (taxonomy_v1.yaml) that defines every harm mechanism, its detection weight, and its decision threshold. Every classification result is stamped with the taxonomy version it was produced under, so results stay reproducible even as the taxonomy evolves.
  • Severity ladder — a simplified ordering of harm mechanisms from least to most severe (none → narrative_distortion → demonization/objectification → animalization/criminalization → direct_call_to_violence), used only for escalation tracking. It is a project-specific model inspired by general atrocity-escalation literature, not a validated academic scale — see Escalation-Chain Tracking.
  • Source — an arbitrary identifier you choose (an account handle, a URL, a document ID) that ties a sequence of classified texts together so escalation can be tracked across them.
  • Benchmark test type — a label on each benchmark case describing what capability it tests (does the engine handle negation? counter-speech? disguised spelling?), so a single aggregate accuracy number can't hide a specific, important blind spot. See Benchmark Suite.
  • Language confidence — every classification is tagged verified (English, Spanish, French, Russian, Arabic — well-resourced languages with the same detection rigor) or experimental (Igbo, Yoruba, Hausa — a seed vocabulary, not native-speaker-reviewed). See Multilingual Support.
  • Dog-whistle — a coded term with a specific, documented bigoted meaning ("globalist" as an antisemitic conspiracy trope) that reads as innocuous to anyone unfamiliar with it. Detected as an additional signal source alongside the taxonomy, not a separate system. See Dog-whistle Lexicon.
  • Content hash / record hash — a SHA-256 fingerprint of what was classified (content_hash) and, for tracked sources, a hash chain over the observation history (record_hash) that makes tampering with a historical record detectable. See Provenance & Tamper-Evidence.