Bibliographic record
Abstract
According to Porter and Brown, multilateral environmental negotiations involve four phases, namely issue definition, fact-finding, bargaining, and regime strengthening. Scientific investigations and their results can play an important role in these four different phases. However, a review of most of the multilateral environmental negotiations since the 1972 Stockholm conference shows that in most cases scientific evidence has been of limited value or even irrelevant. There are several reasons for this, but probably the most important one is related to scientific uncertainty hovering over environmental negotiation. Due to such uncertainty, scientific findings are easily subject to manipulation for extraneous ends. Moreover, scientific uncertainty allows political actors to exercise greater control over decision making. Therefore, in order to make environmental negotiations proceed upon scientific evidence, it is crucial to handle uncertainty properly. One way of handling uncertainty is to promote research cooperation. It is also important to give science its due, and maintain a balance between science and politics. Moreover, new environmental treaty-making techniques should be explored. Montreal Protocol is probably the best example of science playing a major driving force behind political action. Four major scientific discoveries were to influence the negotiation process. Some important lessons can be learned which should be applied to other multilateral negotiations. For instance, agreements should be made flexible enough to accommodate new scientific information. To assure the acceptance of scientific data, scientists must be perceived as unbiased and nonpartisan. Scientific working groups and workshops between politicians and scientist should be a part of the negotiation process.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".