Bibliographic record
Abstract
In January 2020, a divided 9th Circuit Court of Appeals dismissed the long running case, Juliana v. United States. The plaintiffs, 21 young citizens and an environmental organization, had sued the U.S. president and various federal agencies, claiming that their continued authorization and subsidization of fossil fuels contributed to catastrophic climate change that was incompatible with sustained human life. They argued that these harms constituted a violation of their constitutional rights to due process and equal protection of the law, and sought declaratory relief as well as an injunction requiring the government to phase out fossil fuel emissions and draw down excess carbon dioxide emissions. The appeals court, like the District Court below, agreed with the plaintiffs that the evidence filed “leaves little basis for denying that climate change is occurring at an increasingly rapid pace” and that “this unprecedented rise stems from fossil fuel combustion and will wreak havoc on the Earth’s climate if unchecked”. The Court also accepted the plaintiffs’ expert evidence that “the federal government has long promoted fossil fuel use despite knowing that it can cause catastrophic climate change”. In the end, however, the majority concluded that the claims were not justiciable in that it was beyond the power of the court to order, design or supervise the plaintiffs’ requested remedy. The panel “reluctantly concluded that the plaintiffs’ case must be made to the political branches or to the electorate at large”.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.042 | 0.006 |
| Scholarly communication | 0.008 | 0.001 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.020 | 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".