Mexico's Pivotal Democratic Election. Candidates, Voters, and the Presidential Campaign of 2000
Bibliographic record
Abstract
Mexico's Pivotal Democratic Election. Candidates, Voters, and the Presidential Campaign of 2000, Jorge I. Domínguez and Chappell Lawson, eds., Stanford and La Jolla: Stanford University Press-Center for U.S.-Mexican Studies, University of California, San Diego, 2004, pp. xxiv, 363. This book reads almost like the dissection of one single day: July 2, 2000, when Vicente Fox was elected president of Mexico. As an opposition candidate, Fox defeated the PRI, the party that had been in power for the longest period in modern world history. The title of this book is thus aptly chosen, because that day Mexican politics changed forever. It captures the uniqueness of that moment. Even if Fox's victory is understandable in retrospect, most analysts could not predict it. Indeed, as the events were unfolding, not even Fox himself was certain about the outcome. Francisco Labastida, PRI's candidate, was, until the last moment, certain he would win.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".