Governance-weighted criticality

The same supply concentration is more dangerous when the producers are badly governed. Here I re-weight every material’s concentration by the governance of its producers — and watch the risk list reorder.

How it’s built

Each producer gets a governance-risk weight g = (2.5 − WGI)/5 from the World Bank Worldwide Governance Indicators, which feeds a governance-weighted concentration score Σ shareᵢ²·gᵢ. From that I build an EU/SCRREEN-shaped supply-risk proxy (bottleneck-stage governance-weighted concentration, discounted by recycling, scaled by substitutability) and a Graedel-style supply-risk axis — both set beside my own index.

These are proxies on public approximations, not the official EU or Yale scores (which use CRM-specific, stage-granular, expert-weighted inputs) — read it as a governance lens. Depletion-time and environmental axes are omitted (no tonnage/LCA data), and production concentration uses top-N mine shares. Computed by build_criticality.py from public data.

The rankings sit in the same family — Spearman ρ +0.77 (EU-shaped vs our index), +0.66 (Graedel-shaped vs ours), +0.86 (the two proxies) — but this is partly mechanical: all three share inputs (concentration, recycling, substitutability), so read it as "same family", not independent validation. What the governance weighting changes: it pushes up materials with a high-governance-risk producer in the mix — Cobalt oxides & hydroxides (🇨🇩Congo [DRC] g0.82), Aluminium ores / bauxite (🇬🇳Guinea g0.71), Tantalum, unwrought (🇨🇩Congo [DRC] g0.82), Palladium, unwrought (🇷🇺Russia g0.69), Nickel, unwrought (🇵🇭Philippines g0.57) — and down those mined in well-governed countries — Lithium carbonate (🇦🇺Australia g0.19), Strontium carbonate (🇪🇸Spain g0.35), Helium (🇺🇸United States g0.32), Hafnium, unwrought (🇦🇺Australia g0.19), Coking coal (🇦🇺Australia g0.19).

#	Material	EU-SR	Graedel	ours	producer risk	gov. effect
1	Gallium ⛓	100	88	57	🇨🇳 0.54	·
2	Beryllium, unwrought	81	72	76	🇺🇸 0.39	·
3	Cobalt oxides & hydroxides	68	77	43	🇨🇩 0.78	▲ 7
4	Ferro-niobium	62	77	63	🇧🇷 0.52	·
5	Natural graphite	59	77	52	🇨🇳 0.57	·
6	Magnesium, unwrought	55	75	61	🇨🇳 0.55	·
7	Phosphorus	50	76	62	🇨🇳 0.54	·
8	Rare-earth permanent magnets	48	75	52	🇨🇳 0.54	·
9	Silicon, < 99.99%	48	74	46	🇨🇳 0.54	·
10	Aluminium ores / bauxite	44	57	46	🇦🇺 0.48	▲ 5
11	Germanium ⛓	43	72	44	🇨🇳 0.55	·
12	Platinum, unwrought	39	72	40	🇿🇦 0.56	·
13	Fluorspar, >97% CaF2	35	71	48	🇨🇳 0.56	·
14	Ferro-vanadium	35	70	47	🇨🇳 0.57	·
15	Lithium carbonate	34	64	62	🇦🇺 0.37	▼ 10
16	Tungsten, unwrought	34	68	46	🇨🇳 0.55	·
17	Natural borates	31	62	42	🇹🇷 0.51	▲ 2
18	Tantalum, unwrought	29	70	33	🇨🇩 0.66	▲ 4
19	Manganese ore	25	63	46	🇿🇦 0.50	·
20	Nickel, unwrought	20	62	35	🇮🇩 0.55	▲ 3
21	Palladium, unwrought	18	62	24	🇷🇺 0.59	▲ 4
22	Helium	18	68	22	🇺🇸 0.39	▼ 5
23	Phosphate rock	13	62	34	🇨🇳 0.53	▲ 3
24	Strontium carbonate	10	63	55	🇪🇸 0.55	▼ 6
25	Antimony, unwrought	9	56	38	🇨🇳 0.61	▲ 2
26	Hafnium, unwrought	9	64	34	🇦🇺 0.36	▼ 5
27	Feldspar	8	51	25	🇹🇷 0.54	▲ 2
28	Arsenic	6	59	28	🇵🇪 0.57	·
29	Coking coal	5	62	24	🇦🇺 0.40	▼ 5
30	Baryte	3	56	16	🇨🇳 0.55	·
31	Titanium, unwrought	1	52	39	🇨🇳 0.52	·
32	Refined copper cathodes	0	50	23	🇨🇱 0.53	·

⛓ gallium and germanium share one HS6 code (811292; hafnium is separate). WGI: World Bank (mean of 6 estimates). Computed from data.json + wgi.json → criticality.json.

Concentration in risky places