Saving Ourselves: Interviews with World Leaders on the Sustainable Transition
Bibliographic record
Abstract
"Sustainability is going to be one of the most important issues of the coming decades. For the first time, institutions at all levels, public and private, national and international, are teaming up to combat climate change and to promote more sustainable societies. In this book, Yacine Belhaj-Bouabdallah interviews heads of states, politicians, religious leaders, leading academics, diplomats, CEOs, and heads of NGOs to make the challenges and solutions facing us more understandable to everyone. Covering issues such preserving biodiversity, improving our food systems, building sustainable cities, and promoting good governance, Saving Ourselves aims to show that though we are facing some unprecedented challenges, we are also at a critical point in time to take advantage of all the opportunities sustainable development provides. Through interviews with 90 world leaders, this book sheds light on the different arguments presented in the fight to save our planet. The contributors include, Prime Minister Justin Trudeau of Canada, President Michelle Bachelet of Chile, Prime Minister Sheikh Hasina of Bangladesh, President Ameenah-Gurib Fakim of Mauritius, President Marie Louise Coleiro Preca of Malta, Prime Minister Enele Sopoaga of Tuvalu, 6 former heads of states/governments, 5 mayors, 7 ministers, 2 Nobel Prize winners, leading academics, and the heads of organisations such as WWF International, Oxfam International, the IUCN, Unilever, and the World Business Council on Sustainable Development."--Publisher's website
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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".