Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
President Obama received approximately 51.5% of the two-party vote in the 2012 election. The last Bread and Peace Model forecast of Obama's vote share, based on advance estimates of 2012:quarter 3 personal income posted on October 26, 2012, by the Bureau of Economic Analysis (BEA), was 46.6%—lower than the 47.5% forecast appearing in the October issue of PS , which was based on July 27, 2012, BEA data. The Bread and Peace Model therefore underpredicted Obama's vote by 4 to 5 percentage points, equivalent to around 2 model standard errors. The president's vote therefore benefited from a +2-sigma composite shock to Bread and Peace Model fundamentals. Figure 1 shows actual and predicted values for 2012 in perspective of incumbent vote shares at all presidential elections 1952–2012.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it