BEHAVE/BEHAVE-TEXT/attribution-recipes.md

BEHAVE-TEXT Attribution Recipes

This document is not part of BEHAVE-TEXT. BEHAVE-TEXT (scratchpad.md) defines the observation taxonomy and emission envelope. It does not assert who an actor is, link sessions, or assign profiles. Those are attribution-engine concerns.

This document is a placeholder. Recipes for the text domain wait for corpus calibration. The Rutify Telegram corpus (forthcoming) will be the labeling ground truth that drives the first concrete profiles.

---

What goes here eventually

When BEHAVE-TEXT has a calibrated corpus, this document will mirror BEHAVE-SHELL's attribution-recipes.md structure:

1. Engine Interface — what the engine consumes from BEHAVE-TEXT (actor.observation.text.* topics) plus user-supplied labels (identity.label.applied); what it emits (attribution.profile.candidate, attribution.profile.current, attribution.linkage.proposed).
2. Profile Recipes — observation-pattern definitions for each text-domain operator class. Likely starting points based on the Rutify domain:
   • credential_broker — high transactional_language, high boasting_pattern, broadcast attention_pattern.
   • low_skill_buyer — low vocabulary_richness, slow response_latency, high question_formation_style:lexical.
   • group_admin — high conversation_initiation_rate, focused attention_pattern, high opsec_awareness.
   • lurker_or_observer — minimal message volume, near-zero conversation_initiation_rate.
   • bot_or_automated_poster — perfect punctuation_style consistency, no typo_signature, machine-pasted message_length distribution.
3. Linkage Rules — rules for proposing identity links across accounts based on stylometric signature similarity. The function_word_distribution simhash is the load-bearing primitive here (Hamming-comparable across sessions, hard to consciously fake).
4. User-Owned Topic Schemas — identity.label.applied and identity.engagement.authorized schemas for the text domain.

What stays out

Same boundary as BEHAVE-SHELL's recipes: profiles describe observation patterns, not operator types. Engines combine BEHAVE-TEXT primitives with BEHAVE-SHELL primitives (when the same identity appears in both substrates) and with user-supplied labels to produce attribution.

Status

Empty until the Rutify corpus is processed. Adding speculative recipes here without corpus validation would repeat the v0.1 mistake of emitting confidently-wrong observations. The five labelled BEHAVE-SHELL sessions (HUMAN, YOU-sim, LW-sim, CLAUDE-FF, CLAUDE-CL) are the model: profiles get written after a labelled calibration grid exists, not before.