Biophysical economic interpretation of the Great Depression: A critical period of an energy transition
Bibliographic record
Abstract
Abstract The objective of this paper is to explain the cause and proceedings of the 1930s Great Depression from a biophysical economic perspective. The Depression was a painful episode in the socio‐technological transition from a coal/railroad regime to one based on hydrocarbons, motor vehicles, and electricity. The beginning—the Great Crash of October 1929—corresponded with drastic cuts in oil prices and announcement of oil supply certainty, following discovery of huge oilfields in the US Southwest. The Depression principally centered on a change from railroads to motor‐vehicle‐based transportation, but was long and drawn‐out due to the hegemonic power that the railroads held over the US economy. The late 1920s saw increased use of hydrocarbon‐based technologies, but the emerging technologies were still reliant on the old technological system. Methods of biophysical economics, mapping energy flows to capital formation, show the critical role of railroads in the Depression. In 1929, railroads accounted for 24% of the non‐residential capital stock; they delivered between 70% and 76% of energy needs; and 69% of energy required for capital formation. Thus a hypothesis emerges that dwindling investment in the railroads was a major constraint on the economy. In biophysical terms, the US economy's main energy delivery system—coal carried by railcars—was hamstrung. Energy flow Sankey diagrams for 1929 and 1939 show the gradual change in energy systems that occurred over the Depression.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".