Behavioral Signature · Oversight view

Susan Collins

elected official · U.S. Senate, Maine
Methodology — read this first. This page borrows the cross-domain signal-harvesting mechanic that Cambridge Analytica pointed at private citizens, and points it back at public figures via public records — with the output oriented at citizen oversight infrastructure, not persuasion. Every metric below is a sourced count or ratio drawn from primary public records. No metric on this page measures psychology, personality, motive, or intent. The platform documents conduct, not interior state. See methodology for evidence-tier definitions.

S1 // Signature axes

6 numeric structural metrics · each is a sourced count or ratio · derived in code, no LLM interpretation
Behavioral signature radar chart for Susan Collins Doc Density 72 facts Conduct Contradiction 0/0 broken Inferential Dep. 12/72 Network Centrality 191 conn · 186 ctp Capital Flow in $0.0M / out $0.0M Structural Density 2 findings 255075100
AxisScoreUnderlying counts
Documentation Density71/10072 sourced facts · log-scaled (100 ≈ 600 facts)
Conduct Contradiction0/1000 broken / 0 resolved promises
Inferential Dependency17/10012 inferential / 72 total facts · lower = more primary-sourced
Network Centrality100/100191 connections to 186 distinct entities
Capital Flow Asymmetry50/100incoming $0.00M / outgoing $0.00M · 50 = balanced
Structural Finding Density8/1002 structural findings (0 loops + 2 contradictions + 0 promises)

S2 // Structural cluster side-by-side view ↗

5 eligible entities ranked by cosine similarity over the 6-axis signature vector · uses behavior only, not connection-density · JSON export ↗

Cluster membership is a structural observation about documented behavior, not a claim of social affinity or coordination. Two entities share a cluster when their 6-axis behavioral signatures point in the same direction, regardless of whether they have any connection to each other.

  • Thom Tillis 99.9% similarity
    elected official · U.S. Senate, North Carolina
    DOC 69 CON 0 INF 20 NET 100 CAP 50 STR 5
  • Gary Peters 99.9% similarity
    elected official · U.S. Senate, Michigan
    DOC 74 CON 0 INF 14 NET 96 CAP 50 STR 10
  • J. French Hill 99.9% similarity
    person · US Representative (R-AR-2)
    DOC 68 CON 0 INF 22 NET 100 CAP 50 STR 10
  • Robert Menendez 99.8% similarity
    person · US Representative (D-NJ-8)
    DOC 70 CON 0 INF 24 NET 100 CAP 50 STR 4
  • Ryan Mackenzie 99.8% similarity
    person · US Representative (R-PA-7)
    DOC 68 CON 0 INF 8 NET 99 CAP 50 STR 10

S3 // Documented pattern reads across the cluster

backward-looking · count-anchored · no forecasts · methodology-locked prose template

Each observation below is a sourced count across the 5 cluster members — what has been documented to date, never a prediction. The platform does not infer what Susan Collins or anyone else in the cluster will do next.

  • Cluster members with at least one closed loop documented
    0 of 5 (0%)
  • Cluster members with at least one contradiction on record
    5 of 5 (100%)
  • Cluster members with at least one documented broken promise
    0 of 5 (0%)
  • Cluster members whose tracked money-flow chains show net inflow
    0 of 5 (0%)
  • Cluster members whose record is >25% inferential (thinner documentation)
    0 of 5 (0%)
What the prose template enforces:
  • Only past-tense observations of what HAS occurred, never future-tense predictions of what WILL occur.
  • Count-anchored ("M of K") so the operator can verify by going to each linked entity's profile.
  • Cluster-level only — never attributed to any single member.
  • Code-generated from raw counts; no LLM-written prose interpretation.

S4 // Citizen oversight surface

where the inversion happens · same data, pointed at accountability infrastructure

For an entity of this type, the following public oversight tools apply. Each link goes to a primary-source government or registered-nonprofit portal — no third-party intermediaries. Where this entity appears in the underlying records, you can pull the documentation yourself.

// What this page does NOT do

methodology humility · required on every behavioral signature
  • Does NOT measure psychology, personality, or any "Big Five" / OCEAN trait.
  • Does NOT predict what Susan Collins will do. Every axis is backward-looking.
  • Does NOT cluster entities for the purpose of guilt by association. Clustering, when added in a future phase, will use behavioral-signature similarity only, never co-affiliation.
  • Does NOT target private individuals. The page is gated to entities flagged as public figures or registered legal entities.
  • Does NOT generate prose interpretation of the metrics. Every score is a count or ratio with the underlying numbers visible — no LLM-written "what this means" paragraph.
Behavioral Signature · derived from data the platform currently holds for Susan Collins. Scores recompute on each request. Corrections / disputes: [email protected].