ClaimsNate Silver

“it’s hard to make inferences from early voting and attempts to do have a fairly bad track record — as they did this year.”

Nate Silver, editor in chief, writing in FiveThirtyEight article November 2016 Why FiveThirtyEight Gave Trump A Better Chance Than Almost Anyone Else (FiveThirtyEight) archived copy

Factual AI timelines and forecasting

Inferences from early voting data have a fairly bad track record in predicting election outcomes, including in 2016.

Unresolvable The public record could not settle it.

Factual: Statements about the present or the past, checked against the record: did they hold up?

The second judge would not resolve this claim; the verdict shown is the first judge's.

Said for an organisation they lead or work for; it counts on both records.

What would count as true or false

Judge as of November 2016. True: evidence from analysts or academics shows that predictions based on early-vote data have a historically poor or unreliable record, and that prominent early-vote inferences in 2016 pointed the wrong way, e.g. claims that early-vote data showed Clinton winning Florida or North Carolina. Mostly true: the general poor record is supported and 2016 inferences were mostly wrong, but some notable early-vote readings were accurate (e.g. Nevada). Mixed: the evidence on the track record is balanced, or 2016 early-vote inferences were about as often right as wrong. Mostly false: early-vote inferences have a reasonably good record and the 2016 failures were isolated. False: early-vote inferences have been generally accurate, including in 2016.

Set before the research began.

Evidence (8)

  1. E1 Early Voting a Poor Predictor of Final Results | RealClearPolitics RealClearPolitics · 2 November 2016

    “Second, predictions from early voting have a decidedly mixed track record.”
  2. E2 Early Voting a Poor Predictor of Final Results | RealClearPolitics RealClearPolitics · 2 November 2016

    “But if predictions from 2012 were iffy, predictions from 2010 and 2014 were awful.”
  3. E3 Early voting in Nevada looks very good for Democrats Vox · 3 November 2016

    “Now, a gigantic caveat: Early voting does not have a long history in the United States. Any time you make assertions about presidential election outcomes, you are stuck dealing with small sample sizes.”
  4. E4 Do the Early-Voting Patterns in Florida Mean Clinton Will Win? New York Magazine (Intelligencer) · 7 November 2016

    “All in all, Florida will remain a mystery until Tuesday.”
  5. E5 So far, early voting looks like good news for Hillary Clinton Vox · 27 October 2016

    “The relationship is positive, but it’s pretty noisy. In other words, knowing how a party is doing in early voting doesn’t tell you much about how it will do once all the votes are counted.”
  6. E6 So far, early voting looks like good news for Hillary Clinton Vox · 27 October 2016

    “Democrats maintained substantial leads among early voters in North Carolina, Louisiana and West Virginia, and were trailing by a relatively narrow margin in Oklahoma, but still lost those states when all the votes were counted.”
  7. E7 Early voting: Record levels in 2016 may give Clinton edge Associated Press (via Fox 4 News) · 7 November 2016

    “In Florida, a record 6.4 million early ballots are already in, or more than three-fourths of the expected vote. Democrats are ahead, 39.9 percent to 38.5 percent.”
  8. E8 Minorities are a huge force in the early vote — and this year Latinos are making their mark Vox · 7 November 2016

    “In Nevada, a surge in the last few days of early voting made the state, according to state politics expert Jon Ralston, all but unwinnable for Republicans.”

Reasoning

The evidence supports a mixed-to-poor general track record for early-vote predictions (E1, E2, E5, E6). It also shows that 2016 early-vote readings favoured Democrats in Florida and Nevada (E3, E7, E8). However, no evidence item gives the 2016 final results, so the evidence cannot show whether the 2016 early-vote inferences were right or wrong, as the criteria require.

Cite this claim

Nate Silver, “Inferences from early voting data have a fairly bad track record in predicting election outcomes, including in 2016.” (said November 2016). Verdict: unresolvable. Reliability API, claim c_7830489b577c, method 0.1.0+28da144b, dataset release v1.1.2. https://epistacklabs.com/claims/c_7830489b577c

This claim is in dataset release v1.1.2, with the same verdict.

Reply to this claim

For Nate Silver, or someone speaking for them: a correction or counter-evidence. Replies are read before anything is shown; an approved reply shows your name, role, date, statement and link. Your email address is never shown and is deleted 30 days after the decision (privacy).

More factual claims by Nate Silver

  1. Resolved true Factual 8 September 2023
    “It’s not hard, for instance, to find polls from this point in 2015 showing Hillary Clinton with double-digit leads over Trump.”

    Polls from around September 2015 can be found showing Hillary Clinton with double-digit leads over Donald Trump.

  2. Mostly true Factual 21 May 2022
    “There was never any spike in Biden's approval rating.”

    Joe Biden's approval rating never had a spike.

  3. Resolved true Factual 9 June 2021
    “This is the pollster that had shown a big bounce for Garcia before, so either that previous poll was an outlier or her momentum has been usurped by Wiley.”

    A pollster that earlier showed a big bounce for Garcia has now shown a result implying either that the earlier poll was an outlier or that Wiley has taken over her momentum.

  4. Mixed Factual November 2016
    “Instead, there was a modest polling error, well in line with historical polling errors, but even a modest error was enough to provide for plenty of paths to victory for Trump.”

    The 2016 polling error was modest and in line with historical polling errors, yet large enough to give Trump many paths to victory.

  5. Mostly true Factual November 2016
    “The single most important reason that our model gave Trump a better chance than others is because of our assumption that polling errors are correlated.”

    The main reason FiveThirtyEight's 2016 model gave Trump a better chance than other models was its assumption that polling errors are correlated.

All of them

Verdicts are made automatically; how verdicts are made.