Current Trends in Latin American Commons Research
Bibliographic record
Abstract
A lo largo de las diversas regiones y países que componen América Latina existe escaso conocimiento sobre los bienes comunes, y la investigación sobre los mismos. Este trabajo se refiere a esta brecha del conocimiento mediante una revisión de datos sobre la tenencia comunal de la tierra en la región, seguido de un análisis de las publicaciones académicas y presentaciones en congresos internacionales durante el período 1990–2012. Se muestra que la producción académica en Latino América, si bien está creciendo, se encuentra concentrada, relativamente, en un pequeño número de países. Se especulan las razones para ello e identifican los desafíos que necesitan atenderse para que la investigación sobre los bienes comunes pueda prosperar en la región y maximizar su impacto académico y sobre las políticas públicas.
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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.030 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.033 | 0.004 |
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".