Socio-Analogs Evaluation Rubric (v0.3)

The Socio-Analogs Rubric walks you through 10 criteria—mechanistic fidelity, scale alignment, data tractability, intervention leverage, ethical risk, and more—so you can grade any systems model-to-society analogy. Use it to fill modeling gaps in “soft” sciences.

Criteria

#	Criterion	What it tests	Weight
1	Mechanistic fidelity	Does the causal chain inside the analog genuinely mirror the target phenomenon?	0.20
2	Variable coverage (P S C A)	Can you map all four state-variables—Pressure, Symbolic entropy, Coherence, usable ATP—without hand-waving?	0.20
3	Scale alignment	Does the spatial / temporal scale of the analog match the target system?	0.10
4	Pathology isomorphism	Do the failure modes line up (build-up, inflammation, brittle snap, etc.)?	0.10
5	Intervention clarity	Does the analog naturally suggest concrete levers or checkpoints?	0.10
6	Empirical resonance	Is there solid data on the analog’s behaviour in its native field?	0.10
7	Communicative vividness	Can a lay stakeholder grasp it in < 30 s and recall it a week later?	0.05
8	Distortion risk	How likely is the metaphor to mislead? (Low risk = high score)	0.05
9	Composability / extensibility	Can the analog nest or layer with others without contradiction?	0.05
10	Novelty vs. redundancy	Does it add distinct explanatory power beyond analogs already in play?	0.05

Scoring formula

Confidence = Σ(weight × score (1-5)) × 20 → range 0-100

Confidence bands

• 85 – 100 → Tier 1 (flagship)
• 70 – 84 → Tier 2 (support)
• 50 – 69 → Tier 3 (context)
• < 50 → rethink or drop

Quick way to use the rubric

• Define the target phenomenon in one sentence.
• Describe the candidate analog in ≤ 75 words (keep it concrete).
• Gather 15-30 minutes of references (articles, datasets, case studies) that speak to the ten criteria.
• Rate each criterion 1-5 and jot a one-line justification.
• Multiply each rating by the weight; add them up, then × 20.
• Locate the final score in the bands above to see if your analog ranks Tier 1, 2, or 3.
• That’s it—you now have a transparent, repeatable score you can compare against other metaphors or share with collaborators.