Application of Ecological Footprint Model to Evaluating Ecological Sustainability in Qiandongnan Miao and Dong Autonomous Prefecture
Bibliographic record
Abstract
The model of ecological footprint proposed by William Rees who was an eco-economist in Canada in 1990s is a way to quantitatively measure the sustainable situation in the range of countries,areas and cities.The model of ecological footprint was used to calculate ecological footprint of Qiandongnan Miao and Dong Autonomous Prefecture.It was found that the ecological footprint per capita of the Prefecture from 2003 to 2006 were 1.2005hm2,1.2249hm2,1.2268hm2 and 1.3226hm2 as well as the ecological deficit per capita were 0.3326hm2,0.4873hm2,0.4852hm2 and 0.5660hm2,which indicated that the ecological deficit of the Prefecture rises by year and the social economic development lies in an unsustainable situation.But compared with Guizhou Province and other areas,the Prefecture still belongs to sustainable area.Based on which the methods and measures were proposed to realize the ecological sustainability in the Prefecture.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".