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Cross-System Power Concentration
0 Australian entities scored across 7 public datasets: procurement, justice funding, political donations, charity registry, foundations, evidence programs, and tax transparency. 0 appear in 3+ systems. 0 entities operate through multiple influence channels simultaneously.
Source: AusTender × Justice Funding × AEC Donations × ACNC Registry × Foundations × ALMA Evidence × ATO Tax Transparency. All cross-referenced by ABN.
Highest Cross-System Power
Entities appearing in the most government datasets simultaneously. Power score weights procurement and political donations highest, with bonus points for network breadth (distinct government buyers, parties funded).
| # | Entity | Systems | Dollar Flow |
|---|
The Revolving Door
0 entities operate through 2+ influence channels: lobbying, political donations, government contracts, and/or justice funding. Scored by influence type: lobbying (5×), donations (3×), contracts (2×), funding (1×), plus dollar thresholds.
| # | Entity | Vectors | Contracts |
|---|
Over-Monitored, Under-Funded
Community-controlled organisations appear in more government datasets than average (0 systems vs 0 overall) — but receive a fraction of the money. They are more visible to government, yet less resourced by it.
The Geography of Power
Major cities receive vastly more dollar flow compared to Very Remote Australia. 0 of 0 LGAs score above 50 on our desert index — meaning high disadvantage, low funding, and sparse entity coverage.
Dollar Flow by Remoteness
| # | LGA | Entities | Desert Score |
|---|
7 Datasets. One Map.
$853.6B in AusTender contracts. Who wins government business.
$33.9B in social program funding. Who gets state money.
AEC donation records. Who funds the politicians.
66K ACNC charities. The formal nonprofit sector.
10.8K grant-makers. Who controls philanthropy.
1,155 interventions. What actually works.
24K entities. Who pays tax on their income.
Each dataset is public. Each entity is matched by ABN. CivicGraph is the first platform to cross-reference all seven simultaneously — revealing who appears everywhere, who holds power across systems, and who gets watched but never funded.
Methodology
Entity resolution: Entities are matched across datasets using Australian Business Number (ABN). For justice funding records without ABNs, exact canonical name matching is used as a fallback. 88.6% of justice funding records are now linked to a resolved entity.
Power score: Composite score weighting system presence (3 points per system) plus dollar-weighted bonuses for procurement (>$1M/10M/100M), donations (>$10K/100K), and justice funding (>$1M/10M). Network breadth adds points for distinct government buyers (capped at 10) and political parties funded (capped at 8).
Revolving door score: Weighted by influence type — lobbying (5×), political donations (3×), contracts (2×), funding (1×). Additional points for high-dollar donations (>$100K) and large contracts (>$10M), plus the number of political parties funded (capped at 5).
Desert score: Composite of SEIFA IRSD decile (inverted, 0-100), remoteness category (0-40), entity coverage gap (0-30), and funding gap (0-20). Higher score means more disadvantaged, more remote, fewer entities, and less funding.
Community-controlled: Entities flagged as community-controlled in the entity registry. Includes Indigenous community organisations, community cooperatives, and locally governed service providers.
Limitations: ABN matching misses entities that operate under different ABNs across datasets. Political donations data has a reporting threshold. ATO tax transparency only covers entities above $100M income (or $200M for non-reporting). Board interlock data is limited to ACNC responsible persons for small charities — ASIC officeholder data would significantly expand this coverage.
Explore the Power Map
See these entities on the interactive force-directed graph. Filter by system count, explore connections, and trace power flows across Australia.
Download: Cross-System Power Concentration
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