Bibliographic record
Abstract
Last year’s report made mention of Turkey’s ratification of the Paris Agreement as well as the country’s plans regarding organization of a Climate Council meeting for laying out a roadmap regarding Turkey’s climate change policy. In February, the Climate Council took place, and the advisory decisions published after the meeting include 217 recommendations, which are the outputs of seven commissions ( ). To begin with, the Greenhouse Gas Mitigation-1 Commission delivered recommendations under the policy fields of energy, transportation, and industry. Second, the Greenhouse Gas Mitigation-2 Commission worked on the policy fields of agriculture, land use, land use change, and forestry, waste, and buildings. Third, the Science and Technology Commission focused on the policy areas of climate change, environment, and biodiversity, clean and circular economy, clean, accessible, and secure energy supply, green and sustainable agriculture, sustainable smart transportation, and horizontal policy fields. Fourth, the Green Finance and Carbon Pricing Commission held discussions on green finance as well as carbon pricing and an emissions trading system. Moreover, the Climate Change Adaptation Commission produced recommendations on possible adaptation measures, while the Local Governments Commission focused on the role of local governments. Finally, the Migration, Just Transition, and other Social Policies Commission elaborated on the policy fields of climate induced migration, climate justice, just transition, education and awareness, and health.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.239 | 0.142 |
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".