Bibliographic record
Abstract
In 2011 Barack Obama invited ten distinguished biographers to the White House to ask them one question: which past American president should I emulate? This was not the first time Obama asked scholars this, but the answer he received would differ as presidential legacies waxed and waned. In 2008 Obama chose Lincoln; in 2009, Reagan; and in 2010, Theodore Roosevelt. \n \nPerspectives on Presidential Leadership is an examination of presidential legacy, and in particular an analysis of the first ever UK ranking of American presidents which took place in 2011. In thirteen chapters, thirteen individual presidential administrations are assessed. Some presidents have been considered a success, others a failure; both types are featured in these thirteen case studies in a measured attempt to understand how the perception of presidential leadership evolves, shifts, and contorts across three centuries of American politics. The case studies also derive from the expertise of the collected British, Irish and Canadian authors, all of whom are leading scholars in their fields, and many of which took part in the 2011 survey. \n \nAt a time when understanding presidential legacy is in high demand, this book offers a unique international perspective. Through extended commentary and inter-disciplinary study of the UK perspective it provides groundbreaking research.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".