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 OKANAGAN INDIAN BAND (VERNON | VERNON, BC) received $102M across 29 federal agreements from 5 departments — above the 90th percentile of recipients funded by Indigenous Services Canada | Services aux Autochtones 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).
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 TESLIN TLINGIT COUNCIL (TESLIN, YUKON|TESLIN, Yukon, YT) received $100M across 33 federal agreements from 6 departments — above the 90th percentile of recipients funded by Crown-Indigenous Relations and Northern Affairs Canada | Relations Couronne-Autochtones et Affaires du Nord 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 SEABIRD ISLAND INDIAN BAND (AGASSIZ | AGASSIZ, BC) received $100M across 11 federal agreements from 4 departments — above the 90th percentile of recipients funded by Indigenous Services Canada | Services aux Autochtones 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 Toronto Metropolitan University (Toronto | Toronto, ON) received $100M across 13 federal agreements from 6 departments — above the 90th percentile of recipients funded by Social Sciences and Humanities Research Council of Canada | Conseil de recherches en sciences humaines du 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 Government of Northwest Territories | Gouvernement des Territoires du Nord-Ouest (YELLOWKNIFE | YELLOWKNIFE, NT) received $100M across 5 federal agreements from 3 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 · Large statutory or formula-driven transfers (health, equalisation, infrastructure envelopes) dominate departmental totals and inflate concentration measures without any procurement decision.
The dataset shows MISSISSAUGAS OF SCUGOG ISLAND FIRST NATION (PORT PERRY, ON) received $99M across 27 federal agreements from 3 departments — above the 90th percentile of recipients funded by Crown-Indigenous Relations and Northern Affairs Canada | Relations Couronne-Autochtones et Affaires du Nord 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 VUNTUT GWITCHIN FIRST NATION (OLD CROW, YUKON, CANADA, YT) received $99M across 47 federal agreements from 7 departments — above the 90th percentile of recipients funded by Crown-Indigenous Relations and Northern Affairs Canada | Relations Couronne-Autochtones et Affaires du Nord 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 SELKIRK FIRST NATION (Pelly Crossing, Yukon, YT) received $99M across 22 federal agreements from 4 departments — above the 90th percentile of recipients funded by Crown-Indigenous Relations and Northern Affairs Canada | Relations Couronne-Autochtones et Affaires du Nord 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 KASHECHEWAN FIRST NATION (Kashechewan | Kashechewan, ON) received $98M across 13 federal agreements from 3 departments — above the 90th percentile of recipients funded by Indigenous Services Canada | Services aux Autochtones 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 Province of New Brunswick|Province du Nouveau-Brunswick (New Brunswick|Nouveau-Brunswick, NB) received $98M across 9 federal agreements from 3 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 · Large statutory or formula-driven transfers (health, equalisation, infrastructure envelopes) dominate departmental totals and inflate concentration measures without any procurement decision.
The dataset shows City of Ottawa (Ottawa, Ontario \ Ottawa (Ontario), ON) received $94M across 14 federal agreements from 4 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).