Lotka's wheel and the long arm of history: how does the distant past determine today's global rate of energy consumption?
Bibliographic record
Abstract
Abstract. Global economic production – the world gross domestic product (GDP) – has been rising steadily relative to global primary energy demands, lending hope that technological advances can drive a gradual decoupling of society from its resource needs and associated environmental pollution. Here we present a contrasting argument: in each of the 50 years following 1970 for which reliable data are available, 1 exajoule of world energy was required to sustain each 5.50±0.21 trillion year 2019 US dollars of a global wealth quantity defined as the cumulative inflation-adjusted economic production summed over all history. No similar scaling was found to apply between energy consumption and the more familiar quantities of yearly economic production, capital formation, or physical capital. Considering that the scaling has held over half a century, a period that covers two-thirds of the historical growth in world energy demands, the implication is that inertia plays a far more dominant role in guiding societal trajectories than has generally been permitted in macroeconomics models or by policies that prescribe rapid climate mitigation strategies. If so, environmental impacts will remain strongly tethered to even quite distant past economic production – an unchangeable quantity. As for the current economy, it will not in fact decouple from its resource needs. Instead, simply maintaining existing levels of world inflation-adjusted economic production will require sustaining growth of energy consumption at current rates.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.010 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".