Bibliographic record
Abstract
Probablemente sea aún muy pronto para llegar a cualquier conclusión definitiva sobre el efecto de los ajustes estructurales a la distribución de ingresos y su efecto sobre la evolución de la pobreza en América Latina; sin embargo, este trabajo intenta evaluar las tendencias arriba mencionadas en siete países lationamericanos durante la década de los ochenta. La evidencia que aquí se presenta apunta hacia una correlación entre los procesos de cambio acelerado en los regímenes de comercio de tales países y una tendencia hacia la concentración de los ingresos. A la vez, este artículo subraya que los países con un proceso gradual de reformas comerciales han mostrado un mejoramiento en su distribución del ingreso.ABSTRACTIt is probably too early to draw any definite conclusions on the effect of structural adjustment in the distribution of income, and the evolution of poverty in Latin America. This paper, however, represents an attempt to assess income distribution trends and the evolution of poverty in seven Latin American countries during the 1980's. The evidence presented here points at a correlation between processes of rapid change in the countries' trade regimes, and a tendency toward the concentration of income. At the same time, this article emphasizes how countries with a gradual process of trade reform have shown an improvement in their distribution of income.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".