Environmental NGOs and the Biosafety Protocol: a case study on political influence
Bibliographic record
Abstract
Abstract It is not only governments which play an important role in securing international agreements, but environmental non‐governmental organizations (ENGOs) as well. This is reflected in the ever‐growing body of literature concerning this topic. This article deals with the political influence of ENGOs on the Biosafety Protocol, a protocol linked to the UNEP Convention on Biological Diversity. It concludes that these organizations did have an impact on the final agreement that was made, with one example being the inclusion of the precautionary principle in the final protocol (although not exclusively determined by ENGOs). They were particularly able to influence policy outcomes by lobbying government delegates, by co‐operating with developing countries and by mobilizing public pressure. With regard to the time frame of the biosafety negotiations, ENGOs succeeded in exercising most of their influence in the so‐called ‘pre‐negotiation’ phase. Copyright © 2003 John Wiley & Sons, Ltd. and ERP Environment.
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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 | 0.018 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.017 | 0.010 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".