The history of net zero: can we move from concepts to practice?
Bibliographic record
Abstract
Net zero has become the new organizing principle of climate politics. Though the adoption of net zero targets has created optimism in the climate regime, there remain significant concerns that it is little more than a vague aspiration. Studies have focused on various net zero definitions, as well as the adoption and robustness of net zero goals. This paper builds on these works by conducting a systematic meta-review of scholarly research on net zero from 1991 to 2021. First, we find that the literature focuses on establishing pathways and creating policies, with much less research on target-setting and implementation. Second, most net zero scholarship focuses on the energy sector, including buildings, while hard to abate sectors are underexamined. Third, there is a disproportionate focus on creating policies for net zero buildings, which are relatively easy to measure and decarbonize compared to other sectors. Finally, there is a notable absence of work on the political factors that enable or constrain the implementation of net zero policies, as well as the efficacy of these policies. This indicates an urgent need for more research on the politics of net zero.
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 | 0.025 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.004 | 0.047 |
| Scholarly communication | 0.013 | 0.034 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.015 |
| Insufficient payload (model declined to judge) | 0.009 | 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".