Regional integration and border interactions in the Cuenca Del Plata: Legacies, achievements and challenges for the Mercosur
Bibliographic record
Abstract
The Cuenca del Plata covers border territories of Argentina, Brazil, Paraguay and Uruguay. In other words, all Mercosur members share cross‐border interests in this border space. Due to the regional integration, borders and border spaces have been to a certain extent redefined. The Cuenca del Plata represents a stimulating case‐study to analyse how and how far the cross‐border public action has been adjusted to this new Mercosur deal. Past and current public policies in the area are analyzed. However, colonial and statenation legacies remain insidious. Accordingly, current intergovernmental architecture in the Mercosur is reflected sharply in current cross‐border regime. Facing this top‐down process, it is crucial to stress bottom‐up efforts from regional and local governments, along with initiatives from the civil society that adopt alternative forms of decision‐making process.
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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 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".