Broadscale Assessment of Groundhog (Marmota monax) Predictions of Spring Onset No Better than Chance
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Groundhog Day is a widespread North American ritual that marks the onset of spring, with festivities centered around animals that humans believe have abilities to make seasonal predictions. Yet, the collective success of groundhog Marmota monax prognosticators has never been rigorously tested. Here, we propose the local climate-predicted phenology of early blooming spring plants (Carolina spring beauty, or Claytonia caroliniana , which overlaps in native range with groundhogs) as a novel and relevant descriptor of spring onset that can be applied comparatively across a broad geographical range. Of 530 unique groundhog-year predictions across 33 different locations, spring onset was correctly predicted by groundhogs exactly 50% of the time. While no singular groundhog predicted the timing of spring with any statistical significance, there were a handful of groundhogs with notable records of both successful and unsuccessful predictions: Essex Ed (Essex, Connecticut), Stonewall Jackson (Wantage, New Jersey), and Chuckles (Manchester, Connecticut) correctly predicted spring onset over 70% of the time. By contrast, Buckeye Chuck (Marion, Ohio), Dunkirk Dave (Dunkirk, New York), and Holland Huckleberry (Holland, Ohio) made incorrect predictions over 70% of the time. The two most widely recognized and long-tenured groundhogs in their respective countries—Wiarton Willie (Canada) and Punxsutawney Phil (United States)—had success rates of 54% and 52%, respectively, despite over 150 collective guesses. Using a novel phenological indicator of spring, this study determined, without a shadow of a doubt, that groundhog prognosticating abilities for the arrival of spring are no better than chance.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it