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Every proposed congressional map should be tested against a published, million-map algorithmic baseline before whichever body, commission or legislature, adopts the final lines.
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Jul 5, 2026
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The party's full position: mandatory algorithmic ensemble analysis as a disclosure and evidentiary layer applied to every congressional map before final adoption, generated from the state's traditional, nonpartisan criteria alone, never the state's own declared political goals, so a state cannot define its own baseline and hide the exact outlier this layer exists to catch, paired with a separate, required race-aware audit that uses racial and language-minority population data specifically to test whether the race-neutral baseline itself undercounts minority-opportunity districts. A third, litigation-specific construction, built to also match a state's specified political goals because Callais requires that of an illustrative map, is what becomes admissible in federal Section 2 litigation; it is distinct from, and never substitutes for, the neutral public baseline. This is backed by federal funding for the technical capacity to run all three analyses. The mechanism is Congress's Elections Clause authority, which lets this apply nationally without dictating which body (legislature, commission, or court-appointed special master) holds final map-drawing authority in any given state. That institutional question, live and unresolved in most states, belongs to a different debate; this position is agnostic about who draws the map and insistent about what has to be shown before whatever body does draw it can make the map final. The method already exists in production use: the Princeton Gerrymandering Project's and RepresentUs's Redistricting Report Card, built on MGGG's GerryChain engine, already grades every state's adopted congressional map against a million-plan ensemble baseline, and has publicly graded maps from both parties. This position asks that what already happens after the fact, voluntarily and for every state, become a mandatory step before final adoption, not a novel technology requiring years of development before deployment.
The narrow, testable claim this position stands or falls on: a computational ensemble comparison should be mandatory as a disclosure input to whoever holds final map-drawing authority, never adopted as that authority itself, and the required second audit, as distinct from the public disclosure baseline (which stays race-neutral by design) and the separate litigation construction (which stays race-neutral because Callais's updated Gingles showing requires it on the merits, not merely to keep the evidence admissible), built to exclude racial and language-minority population data would fail its own purpose, because a race-blind baseline has been shown to systematically undercount the minority-opportunity districts current maps produce. Both halves are falsifiable: the first fails if a state's commission or legislature loses legal authority to depart from the tool's output (it doesn't, under this proposal); the second fails if a rigorous race-blind ensemble were shown not to undercount minority representation, which the available research does not show.
Primary — Privacy, Security, and Trust. The mechanism is specific: a mandatory, published statistical baseline gives the public, courts, and rival campaigns the same evidence about whether a map is an outlier that only well-funded litigants currently get through hired expert witnesses, extending this value's transparency-and-accountability commitment to the single process that most directly determines whether an election is competitive at all.
Secondary — Research, Innovation, and Collaboration. Markov Chain Monte Carlo ensemble sampling is academic infrastructure, built by mathematicians and computer scientists (MGGG at Tufts, the Institute for Computational Redistricting at Illinois) for research purposes, that this position asks to be funded as standing civic infrastructure instead of a resource only well-funded litigation can access.
A tension worth naming rather than skipping past: the racial and language-minority population data this position requires an ensemble tool to use is sensitive demographic information, and mandating its use in a government tool sits in some friction with this same value's other half, data minimization. The tension resolves rather than lingers: this data is already public. The Census Bureau has published block-level population by race specifically for redistricting under Public Law 94-171 since 1975, and every legislature, commission, and court in the country already uses it. This position asks a tool to use data every other participant in the process already has, not to collect anything new.
Neither major party's current position centers this specific proposal. The clearest current Democratic vehicle, the Redistricting Reform Act of 2025 (Sens. Padilla, Warnock, and King, and Rep. Lofgren, introduced September 18, 2025, following H.R. 1's House passage in 2019 and 2021 and its defeat by Senate Republican filibuster), would mandate independent redistricting commissions in every state and ban mid-decade redistricting entirely. It doesn't mention algorithmic ensemble disclosure. Republican-controlled legislatures, meanwhile, have generally opposed federal mandates on redistricting procedure as an intrusion on state authority, a position Missouri's and Ohio's legislative leadership both stated in the current cycle, while relying on the U.S. Supreme Court, a federal institution, to override a federal district court's finding against their own state's map in Texas's case. Both parties' 2025-2026 conduct follows the identical pattern regardless of which one is speaking: draw the most aggressive map current law allows, and invoke whichever court is currently receptive. The Redistricting Report Card's own grades make the point better than a partisan argument could: Texas failed it under Republican control; Illinois, Maryland, New York, and Oregon failed it under Democratic control, in the same cycle.
This platform's delta is a synthesis rather than a position already on offer from either party. It keeps the Democratic instinct toward structural, rules-based reform, but implements the accountability piece through disclosure and evidence rather than a blanket national commission mandate, which lets it apply in every state immediately, including the ones where no legislature currently in power is going to hand away its map-drawing authority. It is a narrower ask than the Redistricting Reform Act, and, for that reason, one with a realistic path to piecemeal adoption rather than needing sixty votes for the entire structure at once.
Minor-party footnote: the Forward Party has staked out the most active minor-party position in the broader redistricting-reform category, centering independent commissions in its platform. It hasn't proposed an algorithmic-disclosure standard specifically, which is the gap this position fills.
The strongest objection: Rucho already told federal courts they will not hear partisan-gerrymandering claims, and Callais just made the surviving Voting Rights Act claims harder to win, requiring a race-neutral illustrative map that also meets the state's own goals and present-day evidence of intent rather than a bare showing of discriminatory effect. A mandatory disclosure requirement generates more evidence for exactly the claim courts have said they won't adjudicate. A critic could reasonably ask what a published statistical outlier score accomplishes beyond a stronger press release, when the body most equipped to act on partisan-fairness evidence has already declined the invitation.
The position holds anyway, for three specific reasons. First, most state courts that have addressed partisan gerrymandering under their own constitutions, unlike the federal courts Rucho bound, have found limits there; ensemble evidence is exactly the kind of evidence Pennsylvania's and North Carolina's courts have already accepted from expert witnesses in redistricting litigation, and a standardized, public version of that evidence lowers the cost of bringing that case in every state with a receptive constitution, not just the ones wealthy enough to hire their own modelers. Second, Callais narrowed Section 2 by demanding present-day evidence of intent rather than a bare effects showing, which makes statistical outlier analysis more relevant to that claim, not less: showing a map deviates further from a race-neutral, criteria-compliant baseline than chance would predict is precisely the kind of current-map evidence a plaintiff needs to establish that a map's shape reflects a deliberate present-day choice rather than an incidental one, and generating the litigation-specific version of that baseline without race as a criterion, while also matching a state's own specified political goals where it has stated any, is what keeps it usable as illustrative-map evidence under Callais's full requirement, rather than excludable on the same ground the state's own racial gerrymander was or dismissed as failing to match the state's stated partisan aims the way Texas's does. Third, human commissions already use statistical fairness evidence today, independent of what any court does with it: Michigan's commission built lopsided-margins, mean-median, and efficiency-gap scoring directly into its own mapping software during the 2021-2022 cycle, evidence aimed at the commission's own legitimacy and internal deliberation, not at a future lawsuit.
One honest, narrow loose thread remains. Callais was decided ten weeks before this issue's last review, and no court has yet ruled on whether ensemble-outlier evidence satisfies its new intentional-discrimination standard in practice, on the three-way split this position uses (a neutral public baseline, a race-aware audit, and a separate litigation-specific construction matching a state's political goals) to keep the public disclosure layer immune from a state gaming its own baseline while still producing evidence usable under Callais, or on how precisely the litigation-specific version should encode a state's specified political goals, since partisan balance and incumbent protection resist the same clean mathematical specification population, contiguity, and compactness get. That is a live, specific, currently unanswered set of questions this position will need to revisit as courts and technical practice both develop, not a reason to doubt the argument built on everything that is already settled.
The most concentrated cost falls on incumbent legislators and parties currently drawing maps without independent scrutiny, in states controlled by both parties: Texas's Republican legislature and Illinois's, Maryland's, New York's, and Oregon's Democratic ones alike lose the informational advantage of being the only party that knows, before anyone else does, how far its map departs from a neutral baseline. This position accepts that loss as its entire point. A map-drawer who currently benefits from that asymmetry is precisely who this proposal is written to constrain.
States and redistricting bodies bear a modest compliance cost to run the analysis, mitigated directly by this position's federal technical-assistance grants and its reliance on GerryChain, an already-built, open-source tool rather than a system any state would need to build from scratch.
A more diffuse and less fully resolved cost falls on communities of interest whose shared identity isn't racial or language-minority and isn't well captured by population, contiguity, or compactness data: an economically interdependent region, a shared occupational community, a rural-urban boundary. Even a version of this tool that correctly includes racial data has no built-in way to weigh that kind of community. This position doesn't leave that gap unaddressed: it requires any federally funded ensemble tool to operate alongside a structured public community-of-interest input channel, modeled on Colorado's existing Redistricting Online public comment portal, so the quantitative baseline has a qualitative counterweight rather than standing alone as the final word on what a defensible map looks like.
Advocacy groups and under-resourced litigants who currently pay for expert witnesses to produce the equivalent analysis case by case are the clearest beneficiaries of this shift. Standardizing the evidence as a public output is the specific mechanism that narrows the resource gap between a well-funded state defending its map and a challenger who cannot currently afford the same modeling.
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