Bibliographic record
Abstract
On 22 April, 1970, the first Earth Day, millions of people took to the streets in cities and towns across the United States, giving voice to an emerging consciousness of humanity’s impact on planet Earth. How has the planet changed over the last fifty years, what will it look like in 2070, and how will our current understanding of Earth’s trajectory map onto the reality that unfolds over the next half century? In his introduction, Tortell outlines the story and motivation behind the present volume, providing a chronological overview of developments in global environmental politics since the first Earth Day. He simultaneously acknowledges the progress we have made in addressing a range of acute environmental problems, and draws attention to the more pernicious threats that have emerged since the first Earth Day. Tortell summarizes the brief which he gave to the contributing authors of Earth 2020, and which resulted in the present volume: to reflect, from their own specialized vantage points, on how Earth and its human inhabitants have changed over the past fifty years, and to consider what the future might look like another in fifty years’ time. The scope of the volume is also delineated – from authors examining biophysical components of the Earth System, to those examining impacts on organisms and ecosystems, to those exploring the shifts in political, legal, economic and media landscapes that have occurred since 1970. Finally, Tortell calls for increased breaking of traditional boundaries, and conversations across domains of expertise, including new multimodal approaches to engage broader audiences who feel increasingly overwhelmed in the age of information overload.
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 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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.118 | 0.003 |
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; both teacher heads agree on what is shown here.
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".