Bibliographic record
Abstract
Regardless of the number of international studies and reports predicting crisis, nothing has stopped decline of ecosystems and natural resources. The most recent reports of the Intergovernmental Panel on Climate Change (IPCC) provide clear warnings that climate change is happening fast. Lyster charts the activity of the international community since the first Earth Day, and demonstrates why and in what respects they have failed. An important first step was the 1987 Brundtland Report, around the same time the IPCC was established to advise the UN on the Earth’s climate. This led to the 1992 UN Conference on Environment and Development, and the 1997 Kyoto Protocol, where developed countries agreed to cap overall emissions by the end of 2012. A major point of contention here was that the Protocol did not require developing countries to meet targets. The 2016 Paris Agreement, which aims to limit the increase in global average temperature, marked the first time that both developed and developing countries are compelled to act. Finally, Lyster explores how efforts to deal with the climate crisis have often been thwarted by domestic election cycles in fossil fuel-developed economies, pointing to a lack of knowledge and/or political will on the part of many politicians to lead a national discussion on the imperative to take action.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.095 | 0.032 |
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".