Great Expectations: Understanding Bali and the Climate Change Negotiations Process
Bibliographic record
Abstract
This article reviews the December 2007 United Nations Climate Change Conference in Bali. It considers expectations for the meeting and whether the event delivered on these expectations. It also evaluates the long‐term context of the meeting and examines the discussions in Bali on the post‐2012 period (when the Kyoto Protocol's first ‘commitment period’ expires). The article finds that the Bali meeting did not necessarily meet public expectations or respond directly to the latest scientific assessments calling for urgent action. However, the article also finds that Bali was successful in the context of the prevailing political and diplomatic realities and the immense complexity of the climate change challenge – a problem that does not lend itself to a ‘quick fix’ solution. The article concludes that Bali produced a solid outcome that gives direction to future talks and sets a clear deadline for their completion. Finally, it argues that, contrary to some experts’ opinion, the lack of detail in the Bali outcome may prove to be a strength rather than a weakness, since it provides flexibility to negotiators as they try to craft a consensus by the end of 2009.
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 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 | 0.026 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.011 | 0.044 |
| Scholarly communication | 0.019 | 0.023 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".