Eco2: a simple index of economic-ecological deficits
Bibliographic record
Abstract
We present the first joint analysis of the ecological-financial deficits of nations and develop a simple index, the Eco 2 index, which is useful in ranking the combined ecological and financial performance of countries.This index includes information on ecological and financial deficits, trade surplus and gross domestic product (GDP) to evaluate the potential impacts of ecological deficits on the overall economic performance of countries.Results show an ongoing trend towards increased ecological deficits, as natural resources are 'traded' for financial gain.We argue that countries cannot run large financial deficits forever without negative economic consequences and that globally, it is likewise impossible to ignore our global ecological deficit in the long run.Ecological deficits can only be temporarily and partially addressed by incurring financial costs through imports, bounded by available resource surpluses of other nations and the fact that some of these services are place-specific.Ultimately, ecological deficits jeopardize ecosystem functions, energy sources and the food security of nations, with direct implications for human well-being.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".