The Paradoxical Malthusian. A Promethean Perspective on Vaclav Smil’s Growth: From Microorganisms to Megacities (MIT Press, 2019) and Energy and Civilization: A History (MIT Press, 2017)
Bibliographic record
Abstract
Prolific energy writer Vaclav Smil’s “Growth: From Microorganisms to Megacities” (MIT Press, Cambridge, MA, USA, 2019) is marketed as the most comprehensive study of the modalities of growth in Earth’s life systems in their many natural, social, and technological forms. While the book reflects Smil’s strength as a polymath, it also brings into focus his Malthusian outlook. Smil’s Malthusianism is puzzling in light of much empirical evidence to the contrary and of his own detailed histories of human technological achievements, including his recent massive synthesis “Energy and Civilization: A History” (MIT Press, Cambridge, MA, USA, 2017). In keeping with Smil’s historical emphasis, in this review essay, the Malthusian assumptions, assertions, and conclusions of these books are challenged through the Promethean insights of numerous writers whose output long predates the modern environmental movement and can thus avoid charges of “greenwashing”. I make a case that, in the context of market economies (i.e., competition, price system, and private property rights), humans’ unique propensity to trade physical goods and to (re)combine things in new ways have long delivered both improved standards of living and environmental remediation. I further suggest that it is not the volume of materials handled, but rather how they are handled that determines the impact of economic growth on the biosphere. While Professor Smil is fond of saying that “numbers don’t lie”, his work illustrates that they are sometimes made to tell an unduly pessimistic story through the intellectual filters created by an author’s assumptions and value judgements.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.022 |
| Scholarly communication | 0.009 | 0.016 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".