Bibliographic record
Abstract
espanolLa llegada al gobierno del Frente Farabundo Marti para la Liberacion Nacional (fmln) en 2009 ha sido un hecho historico para El Salvador, luego de una sangrienta guerra civil y de una larga hegemonia de la derecha. No obstante, este camino de las armas a la batalla democratica institucional conllevo profundos cambios en el interior de una fuerza politica cuyo programa alentaba la construccion del socialismo a partir de un triunfo politico-militar. Hoy esos objetivos parecen lejanos, y el Frente ha pasado a sostener posiciones progresistas pragmaticas, ha devenido un partido electoralmente competitivo y se ha volcado a la gestion estatal. EnglishThe arrival in goverment of the Farabundo Marti Front for National Liberation (Frente Farabundo Marti de Liberacion Nacional, fmln) in 2009 was an historic moment for El Salvador, after a bloody civil war and a long «democratic» hegemony of the Right. Nevertheless, the path from weapons to institutional democratic battles led to deep changes inside the political force whose programme fed the construction of socialism after a political-military triumph. Today these objectives seem far off, and the Front has gone from sustaining pragmatic progressive positions, has become an electorally competitive party and has overturned the state management.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 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".