Old Tip vs. the Sly Fox: The 1840 Election and the Making of a Partisan Nation
Bibliographic record
Abstract
Although much of this book is traditional political history, focusing on a few leaders, Richard J. Ellis also suggests the need to rethink long-held assumptions about the election of 1840. For many historians, this was the “hard cider and log cabin” campaign in which the Whigs stole a page out of the Democrats' playbook. Froth prevailed over substance, lifting William Henry Harrison into the White House. Log cabins on wheels, mile-long processions, endless lyrics praising Tippecanoe (Harrison) and damning Martin Van Buren, attracted voters to the polls—or so the familiar story goes—raising the rate of voter participation from about 57 percent in 1836 to an unprecedented 80 percent in 1840. If not always persuasive, Ellis's argument makes clear scholars should take a second look at this election. To begin with, Ellis offers a new take on the rising rate at which adult white males voted between 1836 and 1840. By...
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 0.001 |
| 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 | 0.004 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".