The Historical Transition from Coal to Hydrocarbons: Previous Explanations and the Need for an Integrative Perspective
Bibliographic record
Abstract
The article deals with the historical transition from coal to oil and natural gas, commonly referred to as hydrocarbons. This transition occurred throughout the industrialized world between the 1940s and 1970s, yet the causes for the shift from coal to hydrocarbons are only marginally understood. Drawing from recent research on historical energy transitions, we examine the takeover of hydrocarbons in the context of the incumbent coal configurations. Building on previous explanations, we identify two analytical perspectives: (1) the view on the overall energy supply system that diversified when hydrocarbons were introduced, and (2) that on the consumers of energy, who replaced coal with hydrocarbon alternatives. The central argument is that the two perspectives need to be integrated to fully understand why hydrocarbons could replace coal. This monumental change in energy history was no simple shift in fuels, but a complex transition that occurred at (1) the level of energy supply, where hydrocarbons became available as alternatives to coal, and (2) the level of energy consumption, where consumers in the areas of railway and maritime transportation, residential heating, industrial production, and electricity generation actively decided to use hydrocarbon alternatives as substitutions for coal.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.005 | 0.037 |
| Scholarly communication | 0.010 | 0.022 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".