Bibliographic record
Abstract
Today, the debates surrounding environmental policies have gained significant prominence which has resulted in the emergence of different policy solutions and approaches that, in some cases, could be perceived as competing. While the role of policy in the environmental transition is well established, there is a broad consensus that no single policy instrument can be successful for all environmental problems in all regions. On the other hand, the economic consequences of environmental policies have proved to be complex and multilayered. Considering the fragmented and region-specific nature of the literature that assesses the effectiveness of environmental policies, this collection aims at providing an integrated reference that features contributions from social scientists, economists, political scientists, and practitioners to expose and explore the economic repercussions and limitations of environmental policies. This introductory chapter provides an overview of the 16 contributions featured in the collection, as well as an overview of the current landscape. This edited collection presents studies focused on the economic repercussions of policies addressing the governance and protection of natural resources, offers an in-depth investigation of policies that address the energy-emissions-economy nexus, and explores solutions toward financing the environmental transition.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.127 | 0.042 |
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".