keep-true-false-forecasting-questions-near-1-1 TEC-0274 · proposedKeep true and false forecasting questions near 1:1
Balance a forecasting question bank so that events that occurred and events constructed as false appear in roughly equal numbers, so the calibration score does not reward default skepticism.
Proposed. Filed by the drafting stage because a paper introduces or tests it. Nobody has vouched for it. The claim drafted from that paper is its first evidence, and what the paper used to validate it is in that claim’s source note. Say whether it held up for you, below.
Balance a forecasting question bank so that events that occurred and events constructed as false appear in roughly equal numbers, so the calibration score does not reward default skepticism. Filed by the drafting stage from SocietyBench: Forecasting Counterfactual Social-World Evolution (2608.04009) with status proposed: the paper introduces or tests it, and the claim drafted from the paper is its first evidence. The paper validated it by: Splitting the calibration bank by answer value showed a six-model mean of 76.1 on false items versus 60.3 on true items; dropping the designed-false subset moved the mean down 3.4 points, identifying it as the easiest subset.. Nobody has vouched for it; add support or contest it on this page.
Does it work?
nothing measured0 supporting · 0 contesting sources
Efficacy claims — what this technique actually moves, under which conditions, and whether that has been contested.
No efficacy claim filed yet. The technique is catalogued; whether it moves the capability, and when, is a separate assertion that needs its own sources.
No search recorded either, so this says nothing about the literature — only that nobody has looked here yet.
Code
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Sources
Whether a technique works is a claim. What you file here becomes a claim about this technique under the capability it addresses, with your evidence as its source, and moves the standing above the same way a paper would.