Bibliographic record
Abstract
Boulding's 1966 paper on the economics of spaceship Earth established the framework for ecological economics and an understanding of economic growth. In ecological economics, economies are conceptualized as open subsystems of the closed biosphere and are subject to biophysical laws and constraints. Economic growth measured as an increase in real gross domestic product (GDP) has generally been associated with increases in the use of energy and materials and the generation of wastes. Scale, composition, and technology are the proximate determinants of environmental impacts. They are often reduced to two: scale (GDP) and intensity (impact per unit GDP). New work described in this paper defines "green" growth as intensity that declines faster than scale increases. Similarly, "brown" growth occurs when intensity declines more slowly than increases in scale, and "black" growth happens when both scale and intensity increase. These concepts are then related to the environmental Kuznets curve, which can be understood as a transition from brown to green growth. Ecological economics provides a macroperspective on economic growth. It offers broad policy principles, and it challenges the primacy of economic growth as a policy objective, but many important questions remain.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".