The study of impact of carbon taxes in thwarting the impending danger posed by the climate change
Bibliographic record
Abstract
The Climate Change is one of the pressing environmental concerns of the Present times. The adverse impact of the global warming is becoming more apparent, in the form of unusual weather events. The danger posed by the Climate Change poses an existential threat to the present world, which can no longer remain unaddressed. The issue has been constantly addressed in different International forums. The Paris Agreement has given impetus to the global efforts by formally adopting the objective of keeping the global temperatures preferably below 1.5 degree centigrade in comparison to the pre-industrial levels. The United Nations adopted the 2030 Agenda for Sustainable Development in 2015. At its heart are 17 Sustainable Development Goals. The SDG 13 is about taking the urgent action on the part of the global community in combating the climate change. In order to attain the objectives of the Paris agreement, the present research will test the effectiveness of the fiscal tools, primarily the carbon tax. The Researcher intends to study the carbon taxes in European Union and Canada. The study will focus on the effectiveness and the viability of the regulations governing the carbon taxes in attaining the 13th Goal set under the 2030 Agenda for sustainable development. The Researcher further intends to propose the policy measures that can be adopted by India for the implementation of the carbon tax, in order to address the threat posed by the Climate Change.
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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".