Running pattern detector against the corpus
The dataset shows entities receiving substantial federal funding with no recorded business identity — recipients the federal government cannot independently identify.
Glassbox surfaces correlations and observations, not findings of misconduct. Severity is a calibrated read on how strongly the dataset matches the pattern definition — a starting point for review, not a verdict.
The match meets the pattern threshold but the signal is the lower band. Normal review queue.
The match exceeds the routine threshold. Worth a closer look — pull the source rows, walk the citation.
The match is in the highest band of the calibrated scale. Recommend: prioritise for active review.
Severity is computed from the detection signal · recipient_business_number IS NULL or a placeholder ('0', all-zeros, '-', 'n/a', 'none') · is_amendment = false · total ≥ p90 of ALL recipient totals within the recipient's primary department AND ≥ $500K floor · publisher batch-report rows excluded · signal = total $
The dataset shows ABORIGINAL SPORT CIRCLE (Ottawa | Ottawa, ON) received $28M across 34 federal agreements from 3 departments — above the 90th percentile of recipients funded by Canadian Heritage | Patrimoine canadien — with no recipient business number recorded; pattern consistent with ghost capacity (entity not independently identifiable in the federal corpus).
Why this may be benign · Identity rests on the legal name alone (no business number); spelling variants can split one entity into several or merge homonyms (KNOWN-DATA-ISSUES F-6, C-3).
Once a match is identified, the dataset suggests these review actions. Glassbox does not prescribe outcomes — these are calibrated options for funders, auditors, and program officers, framed as correlations to investigate.
An entity receiving substantial federal funds without a recorded business number is identifiable only by name string. Verify identity by mapping to corporate / charity registries and adding the BN to the funder's master record.
TRACE's original definition of ghost capacity covers entities with no employees, no addresses, and revenue dominated by government transfers. For these matches, verify capacity (audited financials, employee count, physical presence) before further awards.
What did the entity actually produce for the funding? Pull deliverable reports, site visits, third-party verification. Ghost-capacity is a capacity question, not a fraud claim.
Many matches here are data-entry omissions (BN simply not recorded) rather than substantive ghost capacity. Use this list to clean up master records and tighten future intake.
These are calibrated suggestions, not directives. The dataset shows the pattern; the funder decides the response.
Aggregated from the matches below. Severity bands are calibrated per pattern; counts and dollar totals reflect this snapshot only.
The dataset shows Metis Nation of Ontario Secretariat (Ottawa, ON) received $28M across 5 federal agreements from 3 departments — above the 90th percentile of recipients funded by Employment and Social Development Canada | Emploi et Développement social Canada — with no recipient business number recorded; pattern consistent with ghost capacity (entity not independently identifiable in the federal corpus).
Why this may be benign · Identity rests on the legal name alone (no business number); spelling variants can split one entity into several or merge homonyms (KNOWN-DATA-ISSUES F-6, C-3).
The dataset shows University of Manitoba|Université du Manitoba (Winnipeg|Winnipeg, MB) received $28M across 32 federal agreements from 4 departments — above the 90th percentile of recipients funded by Western Economic Diversification Canada | Diversification de l'économie de l'Ouest Canada — with no recipient business number recorded; pattern consistent with ghost capacity (entity not independently identifiable in the federal corpus).
Why this may be benign · Identity rests on the legal name alone (no business number); spelling variants can split one entity into several or merge homonyms (KNOWN-DATA-ISSUES F-6, C-3).
The dataset shows DUCKS UNLIMITED CANADA (West Amherst, Nova Scotia|West Amherst, Nouvelle-Écosse, NS) received $28M across 93 federal agreements from 3 departments — above the 90th percentile of recipients funded by Environment and Climate Change Canada | Environnement et Changement climatique Canada — with no recipient business number recorded; pattern consistent with ghost capacity (entity not independently identifiable in the federal corpus).
Why this may be benign · Identity rests on the legal name alone (no business number); spelling variants can split one entity into several or merge homonyms (KNOWN-DATA-ISSUES F-6, C-3).
The dataset shows Manitoba Metis Federation (Winnipeg, Manitoba|Winnipeg (Manitoba), MB) received $28M across 32 federal agreements from 5 departments — above the 90th percentile of recipients funded by Department of Housing, Infrastructure and Communities | Ministère du Logement, de l’Infrastructure et des Collectivités — with no recipient business number recorded; pattern consistent with ghost capacity (entity not independently identifiable in the federal corpus).
Why this may be benign · Identity rests on the legal name alone (no business number); spelling variants can split one entity into several or merge homonyms (KNOWN-DATA-ISSUES F-6, C-3).
The dataset shows MANITOBA METIS FEDERATION INC (WINNIPEG | WINNIPEG, MB) received $27M across 15 federal agreements from 3 departments — above the 90th percentile of recipients funded by Natural Resources Canada | Ressources naturelles Canada — with no recipient business number recorded; pattern consistent with ghost capacity (entity not independently identifiable in the federal corpus).
Why this may be benign · Identity rests on the legal name alone (no business number); spelling variants can split one entity into several or merge homonyms (KNOWN-DATA-ISSUES F-6, C-3).