Information, Public Decision-Making, and Climate Change: The Many Roles of Grey Literature
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The far-reaching effects of climate change are among the leading global concerns today. The impacts of changing climate manifest in rising global temperatures (on land and in the ocean), escalating destructive extreme weather events, increasing biodiversity loss, shifting biomes, growing food insecurity, greater health risks (physical and mental), and involuntary migration of people, among other interconnected factors. The complexity of these problems individually and collectively is receiving extensive consideration in research and public arenas. Concerns about the influences of climate change have been increasing since the 1950s and through the last half of the twentieth century scientific understanding reached a consensus of the causes and numerous negative outcomes. The impacts have become clear in the first decades of the twenty-first century. Researchers in many disciplines are cautioning that the world is rapidly reaching a tipping point in the overall health of the planet, after which recovery will be very difficult. In addition, decision makers are grappling with how to evaluate multiple and sometimes competing calls for action and to decide how to address the issues best.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it