An election forecast that’s 50-50 is not “giving up”

Electoral College, “blowout,” and what counts as a mandate

• Commenters disagree whether 2024 was a “blowout.”
• One side: 312–226 in the Electoral College and sweeping all 7 battleground states is electorally substantial and wiped out long‑term Democratic advantages in several states and demographics.
• Other side: a 1.5–1.6% popular‑vote margin is historically very narrow; by that metric and by close state margins, it was a tight race and not a mandate.
• Dispute over whether EC numbers meaningfully reflect “support” versus just tactical success in a few states.

Usefulness and meaning of 50–50 forecasts

• Some argue a 50–50 forecast is honest when races are extremely close and polls sit within margin of error; pushing probabilities away from 50 just to look “decisive” would be less accurate.
• Others say 50–50 often reflects a model collapsing to a safe local minimum, conveying “no useful information” and functionally equivalent to ignorance.
• Several people stress the distinction between “we can’t tell who will win” and “we can tell this is very close,” which still has decision value (e.g., for turnout, personal planning).

Polling methodology, bias, and herding

• Pollsters struggle with nonresponse, unrepresentative samples, and the need to weight by demographics (race, education, turnout models), which some call “race science” and false precision.
• Goodhart’s Law: because pollsters are graded and aggregated, they are punished for outliers and pushed toward herding around consensus.
• Debate over 538’s pollster grading: whether emphasizing relative bias over absolute error systematically down‑weighted some accurate but “off‑trend” firms.
• Ann Selzer’s big miss in Iowa becomes a case study in outliers, reputational risk, and political backlash; disagreement whether it actually “cost her career” or coincided with planned retirement.

Prediction markets vs polls

• Several note betting markets (e.g., Polymarket) moved to ~65–35 for Trump weeks before Election Day and ended very close to the final EC split, based partly on alternative “neighbor expectation” polling.
• Others caution that prediction markets do not generally drift to 50–50; they only cluster there when real uncertainty is high.
• Some compare markets to bookies: odds are driven by flows of money and information, not just “true” probabilities.

Turnout, demographics, and what models missed

• Many emphasize turnout modeling as the hardest part: enthusiasm, suppression, voting rules, and low‑propensity groups can swing results far more than small preference shifts.
• Examples cited: Native American turnout in Arizona affected by new barriers; Biden voters “swinging to the couch”; activation of young, online white men for Trump.
• Question whether any public model captured these dynamics in advance, versus converging to 50–50.

Electoral system and persistent 50–50 politics

• One camp blames first‑past‑the‑post and the Electoral College for structurally forcing two big parties toward ~50–50 equilibrium and maximizing discontent.
• Others defend the two‑party system as simpler than coalition politics, arguing polarization is driven more by media and social networks than by rules alone.
• Some propose reforms: ranked‑choice, proportional representation, stricter supermajority requirements for laws, more direct or “liquid” democracy.

Media incentives and perception of closeness

• Claims that “mainstream media” pretended Trump had little chance are challenged with archived front pages portraying a close race.
• Several argue media and campaigns both benefit from selling elections as razor‑thin to drive engagement, donations, and turnout.
• Polls are seen as double‑purpose: partially informative, partially agenda‑shaping, depending on how uncertainty is presented.