Bibliographic record
Abstract
Energy flow — the capture and transformation of energy, and the output of pollution generated during that process — is essential to increases in complexity, but with the cost of growing disorder, or entropy. In world-systems, energy flow has been, and continues to be, a basis for intersocietal conflict and competition, including unequal exchange that generates inequality in levels of development and ecological degradation across societies. This article builds upon extant research on the role of energy flow in world-systems through an analysis of data on energy use and GDP in the world-system from 1975 to 2005 and for 1975—2004 for CO 2 emissions. Using a panel of 87 countries, a world-system core, semiperiphery, and periphery is generated based on population-weighted energy use. Analysis of energy flows through this world-system provides support for the existence of unequal ecological exchange — the core countries are using more energy, emitting more CO 2 , and attaining more GDP per capita relative to the semiperiphery, with the periphery lagging well behind both. This relationship also holds for net importers of energy as compared to net energy exporters. This demonstrates the inequality in resource use that leads to the development of the core and the underdevelopment of the periphery. But gains are being made by countries in the semiperiphery and periphery relative to the core for both per capita and percentage of world total measures. This potential for development may place the planet in peril, however, as efficiency gains in the core are being offset by growth in emissions by the semiperiphery and periphery.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".