Responding to Climate Change: Governance and Social Action beyond Kyoto
Bibliographic record
Abstract
It has become an accepted wisdom within academic circles and policy discourse that climate change is a global problem in need of global solutions. More than a decade after the formation of the UNFCCC, the Kyoto Protocol was ratiaed by a sufacient number of states to come into effect in February 2005. Strenuous international negotiations have led to the development of important structures and processes to govern reductions in greenhouse gas emissions. Many, however, consider the progress made as grindingly slow and, in the light of scientiac evidence about the rate of change in the global atmosphere and recommendations for the need to reduce emissions by at least 60 percent over the next afty years, inadequate. In the absence of more effective international action, and cognizant of the big task ahead, alternative attempts at climate change governance and social action have emerged. These approaches recognize that international agreements—if implemented—provide only a partial means through which the mitigation of climate change can be directed, and in turn are reliant on actions in a variety of arenas and at different scales to be effectively implemented. They also increasingly recognize the need to respond to and plan for the impacts of climate change, thus opening up new arenas and linkages between science and policy. This special issue of Global Environmental Politics seeks to move beyond the framework of the international political processes within which the climate change issue is frequently discussed to illuminate how climate protection is sought across a myriad of different sites. In seeking to understand responses to climate change, we are interested in “the processes that create the conditions for ordered rule and collective action within the political realm”1—that is those processes which take place within formalized arenas of government/governance
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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.022 |
| Scholarly communication | 0.014 | 0.013 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".