Crisis threatens science progress
Bibliographic record
Abstract
Years of sociopolitical unrest in Nicaragua and Venezuela have given rise to a human rights and humanitarian crisis in Latin America. Last week, the situation in both countries took a serious turn. In Nicaragua, the government began negotiations with the opposition to end the political crisis, while continuing to repress and harass university students and independent media. In Venezuela, the escalating crisis resulted in the blocking and burning of humanitarian aid at the border—a development that was widely condemned by the rest of the world. Political instability and insecurity in both countries have had a disastrous economic impact on many sectors. The human resource base critical for meeting urgent and long-term needs in these societies is being devastated. As scientists who are members of academies that belong to the InterAmerican Network of Academies of Sciences, we are deeply troubled by these situations and call on the global scientific community to show solidarity with the academic communities in Nicaragua and Venezuela.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.005 | 0.017 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".