Simulation Analysis of Policy for Waste Treatment toward a Sound Material-cycle Society in Tokyo
Bibliographic record
Abstract
Enhancing resource productivity is effective to improve trade-off between the environment and economy. For minimizing consumption of natural resources required for economic activities, it is necessary to strengthen both material recycling and energy utilization, which reduce final disposal amount and return waste to economic activities as resource.This study seeks to clarify environmental economic policy for promoting establishment of sound material-cycle society subject to keeping or expanding the regional economic scale, and enhancing the amount of material recycling and reducing greenhouse gas (GHG) emissions. Study area is Tokyo metropolitan area. To reduce GHG emissions and final disposal amount, we consider promoting both material recycling and energy utilization thoroughly. Under these circumstances, we construct an expanded input-output model. The model includes the flows of waste and energy, and emissions of GHG. With restrictions on GHG emissions, Gross Regional Product (GRP) is maximized as the objective function. We quantitatively analyze how much tax and subsidy on discharging waste is required for sound material-cycle society along with analysis on effects of the policy by model simulation.The results show that, with 10 yen/kg tax on discharging waste, final disposal amount per GRP was 11% lower than the baseline case.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".