STRATEGIC ENVIRONMENTAL ASSESSMENT EFFECTIVENESS AND THE INITIATIVE FOR THE INTEGRATION OF REGIONAL INFRASTRUCTURE IN SOUTH AMERICA (IIRSA): A MULTIPLE CASE REVIEW
Bibliographic record
Abstract
Over the last decade, South American countries have been promoting physical integration of the territory in response to regional export-driven industrialisation policies and the global demand for agriculture products, livestock, and energy sources. A prominent example of this is the Initiative for the Integration of Regional Infrastructure in South America (IIRSA), which was launched at the Meeting of South American Presidents in 2000. At the time of writing, 514 infrastructure projects (including roads, pipelines, waterways, dams and telecommunications systems), with an estimated investment of US$69 billion, had been initiated. Importantly, previous similar development processes in the region have caused serious negative environmental and social impacts. Therefore, Strategic Environmental Assessment (SEA) has been mandated to ensure that the social and environmental issues are adequately addressed in the project planning process. This paper identifies the conditions under which: (a) the SEAs of the IIRSA projects have been undertaken, and (b) the Action Plans have been (or will be) implemented. Using case studies, it analyses whether the SEAs that have been carried out for the IIRSA's projects can be considered effective under these conditions. Finally, drawing on the case study findings, potential ways for improving SEA performance and maximising effectiveness in South America are discussed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".