Will Trump pardon Ghislaine Maxwell by the end of 2026? [ resolves 2026-12-31 (178D) ]
Will Trump pardon Ghislaine Maxwell by end of 2026?
polymarket: [C] multiple sources, tie-break·objective outcome methodology ›
markets · by resolution date · marks: daily snapshot
polymarket 1 market
| market | resolves | P(YES) | vol (24h) | vol (cum) | RCG | venue id | ||
|---|---|---|---|---|---|---|---|---|
| Will Trump pardon Ghislaine Maxwell by end of 2026 | 2026-12-31 | 13.0% | $6 | $681K | C | 0x0dc458…fe20 |
resolution architecture
| venue | proposer | source | citation | arbitration | class | analyst notes |
|---|---|---|---|---|---|---|
| polymarket | Whitelisted Proposers | uncommitted | not provided | Optimistic Oracle (UMA) | Other | — |
verbatim rules
polymarket
This market will resolve to "Yes" if Ghislaine Maxwell receives a presidential pardon, commutation, or reprieve from Donald Trump between July 23, 2025 and December 31, 2026, 11:59 PM ET. Otherwise, this market will resolve to "No".
If it becomes impossible for Trump issue a federal pardon, commutation, or reprieve within this market's timeframe, it may immediately resolve to "No".
The primary resolution source for whether a person is pardoned or not will be official information from the US government, however a consensus of credible reporting will also be used.
platform source field
polymarket.resolutionSource → ∅ no committed source — see rules text above sources (2)
- official information from the US government from rules text · editorial
- a consensus of credible reporting from rules text · editorial
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/will-trump-pardon-ghislaine-maxwell/ |
| JSON | REST API for developers | https://api.clearmarket.fyi/v1/events/will-trump-pardon-ghislaine-maxwell |
| MCP | agentic AI tool call (Claude Desktop, Cursor, Continue) | clearmarket.get_event("will-trump-pardon-ghislaine-maxwell") |
| 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-FS08C0B2L6",
"slug": "will-trump-pardon-ghislaine-maxwell",
"question": "Will Trump pardon Ghislaine Maxwell by the end of 2026?",
"category": "politics",
"tags": [
"politics",
"trump",
"presidential-pardon",
"criminal-justice",
"2026"
],
"venues_covered": [
"polymarket"
],
"market_count": 1,
"cumulative_volume_usd": 681290,
"resolution_clarity_grade": "C",
"rcg_score": 76,
"rcg_caps": [
"commitment_uncommitted_placeholder"
],
"resolution_source": null,
"resolution_source_url": null,
"source_status": "no_committed_source",
"source_of_record": null,
"resolution_source_list": [
{
"name": "official information from the US government",
"url": null,
"provenance": "clearmarket_editorial"
},
{
"name": "a consensus of credible reporting",
"url": null,
"provenance": "clearmarket_editorial"
}
],
"arbitration_model": "uma_oracle",
"proposer_model": "managed_whitelist",
"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"
}
}
}