“A Fight between Two Systems of Thought”: Gerald B. Winrod and the Kansas Senate Race of 1938
Bibliographic record
Abstract
One evening in June 1938, the Wichita evangelist Gerald Burton Winrod made a campaign speech before an audience of approximately 450 people in Fremont Park in the city of Emporia, Kansas, as part of his bid to become the Republican nominee for the Senate. Although “Onward Christian Soldiers” blasted from a sound truck before he began, his address focused on the failures of the Franklin D. Roosevelt administration to redress the economic devastation of the Great Depression. The crowd was enthusiastic: “I'm a Democrat, but I want to vote for you in November,” one listener told him afterward. Asked what he thought the chances were for a Republican to unseat the incumbent Democratic senator George McGill in 1938, Winrod replied, “I see a rising tide of reaction against the New Deal in Kansas. It is evident everywhere I go. Although this is an off-election year, it is going to be...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.049 | 0.024 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".