Government employees cut, before March 2027 [ resolves 2027-03-04 (241D) ]
kalshi: [A] single source·objective outcome methodology ›
distribution · by outcome · marks: daily snapshot
kalshi 7 markets
| market | resolves | P(YES) | vol (24h) | vol (cum) | RCG | venue id | ||
|---|---|---|---|---|---|---|---|---|
| > 50000 | 2027-03-04 | 91.0% | — | $2.7K | A | KXFEDEMPLOYE…000 | ||
| > 100000 | 2027-03-04 | 43.0% | $20 | $2.0K | A | KXFEDEMPLOYE…000 | ||
| > 150000 | 2027-03-04 | 23.0% | — | $1.2K | A | KXFEDEMPLOYE…000 | ||
| > 200000 | 2027-03-04 | 19.0% | — | $51 | A | KXFEDEMPLOYE…000 | ||
| > 250000 | 2027-03-04 | 9.0% | — | $93 | A | KXFEDEMPLOYE…000 | ||
| > 300000 | 2027-03-04 | 3.0% | — | $17 | A | KXFEDEMPLOYE…000 | ||
| > 350000 | 2027-03-04 | 3.0% | — | $32 | A | KXFEDEMPLOYE…000 |
resolution architecture
| venue | proposer | source | citation | arbitration | class | analyst notes |
|---|---|---|---|---|---|---|
| kalshi | Exchange Staff | FRED | not provided | Kalshi Staff | Other | — |
verbatim rules
kalshi
If there are more than 50000 federal employees no longer working relative to the December 2025 employee count before January 2027, then the market resolves to Yes.
At the time of issuance, 2.738 Million Federal Employees are reported for the December 2025 figure.
platform source field
kalshi.settlement_sources → "FRED" sources (1) · single authority
- FRED source of record venue-listed
resolution history
| outcome | market | venue | resolved | final price |
|---|---|---|---|---|
| PENDING | Will there be more than 50000 government employees cut before Jan 2027? | kalshi | 2027-03-04 | 91% |
Derived from the platform price + resolution-date snapshot (1 resolved market). PENDING upgrades to a final outcome on the next refresh.
recent wire items
monitoring status: active no active wire
No CM Signal wire has been published for this event yet.
CM Signal’s news-cycle scan surfaces the day’s top stories alongside the prediction markets pricing them. When a story references this event, its wire is published here and links back to this page.
programmatic access · four surfaces, same payload
One canonical record at every surface — embedded JSON-LD, REST, MCP, and /llms.txt.
| HTML | browsers, AI grounded search, crawlers (embedded JSON-LD @type: Dataset) | https://clearmarket.fyi/events/kxfedemployees-27feb/ |
| JSON | REST API for developers | https://api.clearmarket.fyi/v1/events/kxfedemployees-27feb |
| MCP | agentic AI tool call (Claude Desktop, Cursor, Continue) | clearmarket.get_event("kxfedemployees-27feb") |
| AGENT | AI crawler discovery index | /llms.txt |
Snapshot 2026-07-06. Venue data via Kalshi + Polymarket APIs. Editorial fields (tags, editorial_notes) are ClearMarket-drafted with AI assistance under editorial review. Derived fields (venues_covered, resolution_clarity_grade, rcg_score) computed at serve time. Full per-field map in the JSON record under field_provenance.
raw JSON record · same payload returned by REST endpoint {
"event_id": "CM-EVT-RJ91PG43J7",
"slug": "kxfedemployees-27feb",
"question": "Government employees cut, before March 2027",
"category": "economics",
"tags": [
"economics",
"trump-government",
"workforce-reduction",
"federal-employment",
"2026",
"policy-implementation"
],
"venues_covered": [
"kalshi"
],
"market_count": 7,
"cumulative_volume_usd": 6080,
"resolution_clarity_grade": "A",
"rcg_score": 90,
"rcg_caps": [],
"resolution_source": "FRED",
"resolution_source_url": "https://fred.stlouisfed.org/",
"source_status": "platform_named",
"source_of_record": "FRED",
"resolution_source_list": [
{
"name": "FRED",
"url": "https://fred.stlouisfed.org/",
"provenance": "platform_api"
}
],
"arbitration_model": "kalshi_staff",
"proposer_model": "platform_staff",
"field_provenance": {
"question": {
"source": "clearmarket_editorial"
},
"tags": {
"source": "clearmarket_editorial",
"ai_drafted": true
},
"resolution_clarity_grade": {
"source": "derived",
"method": "rcg_v2_7factor"
},
"venues_covered": {
"source": "derived"
}
}
}