Ecopetrol - Petroecuador Oil Spill Response Agreement – Practical Steps to Effective Regional Cooperation
Bibliographic record
Abstract
ABSTRACT In July 1998, there was an environmental emergency caused by an oil spill in an Ecuadorian pipeline operated by PETROECUADOR (Petróleos del Ecuador). One part of the spilled volume reached the Pacific Ocean and the marine currents caused the oil slick to approach the Colombian coast, creating an environmental hazard. ECOPETROL (Empresa Colombiana de Petróleos) activated its contingency plan in the Port of Tumaco to meet the emergency. As a result of the above experience both companies signed a Mutual Cooperation Agreement to Combat and Control Oil Spills Caused by Oil Tankers and Coastal and Marine Oil Facilities, in October 1999. The Agreement was established in order to allow for a quick and effective joint response in emergency situations of this nature. The bilateral agreement is activated when resources, staff and equipment of the affected party are insufficient. At present it is under implementation. In addition, ECOPETROL and PETROECUADOR, as part of the regional cooperation process on oil spill contingency planning led by ARPEL in Latin America and the Caribbean, involved the Agreement in the framework of the environmental cooperation program with the Canadian International Development Agency (CIDA) to optimize such agreement. This bilateral agreement represents the first real case in Latin America in terms of implementation of the Cooperation in the OPRC 90 Convention, through the joint work of government/industry, and serves as an example for the other countries in the Region.
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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 | 0.019 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".