Bibliographic record
Abstract
Abstract Andrés Manuel López Obrador (b. 1953) is the current president of Mexico (for the period 2018–2024). He has been at the forefront of Mexican politics since 2000, having served as mayor of Mexico City between 2000 and 2005, and making three runs for the presidency in 2006, 2012, and 2018 in which he finally emerged victorious. While his detractors consider him a radical leftist in the mold of Venezuela’s late Hugo Chávez, his supporters praise him as a man of the people who fights to bridge the gap between rich and poor. Political preferences aside, the ascent of López Obrador to the presidency of Mexico needs to be understood first and foremost in the context of the country’s democratic transition. This was a protracted process that started in 1977 and concluded at some point between 1997 and 2000, right about when López arrived on the national political stage. The transition leveled the electoral arena and opened up opportunities for electoral competition that López has been able to capitalize on. Ironically, to this day he refuses to acknowledge the democratic improvements that Mexico experienced during its transition, and which allowed his political ascent in the first place.
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.
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 | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".