The end of plenty: the race to feed a crowded world
Bibliographic record
Abstract
When the demographer Robert Malthus (1766-1834) famously outlined the brutal relationship between food and population, he never imagined the success of modern scientific agriculture. In the mid-twentieth century, an unprecedented agricultural advancement known as the Green Revolution brought hybrid seeds, chemical fertilizers, and improved irrigation that drove the greatest population boom in history-but left ecological devastation in its wake. In The End of Plenty, award-winning environmental journalist Joel K. Bourne Jr. puts our race to feed the world in dramatic perspective. With a skyrocketing world population and tightening global grain supplies spurring riots and revolutions, humanity must produce as much food in the next four decades as it has since the beginning of civilization to avoid a Malthusian catastrophe. Yet climate change could render half our farmland useless by century's end. Writing with an agronomist's eye for practical solutions and a journalist's keen sense of character, detail, and the natural world, Bourne takes readers from his family farm to international agricultural hotspots to introduce the new generation of farmers and scientists engaged in the greatest challenge humanity has ever faced. He discovers young, corporate cowboys trying to revive Ukraine as Europe's breadbasket, a Canadian aquaculturist channeling ancient Chinese traditions, the visionary behind the world's largest organic sugar-cane plantation, and many other extraordinary individuals struggling to increase food supplies-quickly and sustainably-as droughts, floods, and heat waves hammer crops around the globe. Part history, part reportage and advocacy, The End of Plenty is a panoramic account of the future of food, and a clarion call for anyone concerned about our planet and its people.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.024 |
| Scholarly communication | 0.021 | 0.020 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".