Not too late changing the climate story from despair to possibility
Bibliographic record
Abstract
Not Too Late brings strong climate voices from around the world to address the political, scientific, social, and emotional dimensions of the most urgent issue human beings have ever faced. Accessible, encouraging, and engaging, it's an invitation to everyone to understand the issue more deeply, participate more boldly, and imagine the future more creatively. In concise, illuminating essays and interviews, Not Too Late features the voices of Indigenous activists, such as Guam-based attorney and writer Julian Aguon; climate scientists, among them Jacquelyn Gill and Edward Carr; artists, such as Marshall Islands poet and activist Kathy Jtil-Kijiner; and longtime organizers, including The Tyranny of Oil author Antonia Juhasz and Emergent Strategy author adrienne maree brown. Shaped by the clear-eyed wisdom of editors Rebecca Solnit and Thelma Young Lutunatabua, and enhanced by illustrations by David Solnit, Not Too Late is a guide to take us from climate crisis to climate hope. Contributors include Julian Aguon, Jade Begay, adrienne maree brown, Edward Carr, Renato Redantor Constantino, Joelle Gergis, Jacquelyn Gill, Mary Annaise Heglar, Mary Ann Hitt, Roshi Joan Halifax, Nikayla Jefferson, Antonia Juhasz, Kathy Jetnil Kijiner, Fenton Lutunatabua & Joseph Sikulu, Yotam Marom, Denali Nalamalapu, Leah Stokes, Farhana Sultana, and Gloria Walton.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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".