The Unfinished Presidencies: Why Incumbent Presidents May Lose Their Re-Election Bids
Bibliographic record
Abstract
With the conclusion of the 2016 presidential election in the US, presidential scholars have shifted their attention not only to the Trump presidency, but also towards his possible re-election campaign. Throughout the history of the United States incumbent presidents have usually won their bid for a second term in office. The presidency offers incumbents several inherent electoral advantages – e.g., party nomination and unified party base, name recognition and political experience, access to government resources. However, some incumbent candidates have been unable to capitalize on these advantages. The current paper analyzes the electoral bids of Presidents Ford, Carter, and Bush, identifying the factors that can invalidate the advantages intrinsic to holding the office of President of the United States. Resumo Com a conclusão das eleições presidenciais de 2016 nos EUA, os analistas têm focado a sua atenção não só na presidência de Donald Trump, mas também na sua possível reeleição. Ao longo da história dos Estados Unidos, os presidentes têm geralmente ganho sua candidatura a um segundo mandato. A presidência oferece aos titulares várias vantagens eleitorais inerentes – por exemplo, nomeação e base unificada do partido, reconhecimento e experiência política, e acesso a recursos governamentais. No entanto, alguns presidents não conseguiram capitalizar nas vantagens inerentes ao cargo. O atual artigo analisa as candidaturas eleitorais dos presidentes Ford, Carter e Bush, identificando os fatores que invalidaram as vantagens intrínsecas à ocupação do cargo de presidente dos Estados Unidos.
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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 | 0.006 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".