Recycling and natural resource extraction: Insights from monopoly and social planner perspectives
Bibliographic record
Abstract
Type of the article: Research ArticleAbstractThe need to understand how recycling can mitigate resource scarcity has been intensified by the accelerating depletion of natural resources, driven by population growth. In this context, the influence of recycling on the dynamics of natural resource extraction is examined. Through a two-period theoretical model, two settings are considered: one in which profit is maximized by a monopolist, and another in which social welfare is maximized by a social planner. In both cases, a perfectly competitive recycling sector is assumed to operate in the second period, and cost interactions between the initial extraction and recycling activities are explicitly incorporated. It is shown that recycling reduces the second period extraction. In the monopoly case, the initial extraction is reduced under incomplete recycling when marginal recycling costs are high, while its effect becomes ambiguous when these costs are low; under complete recycling, the initial extraction is always reduced. In the social planner case, the initial extraction is found to be reduced under incomplete recycling, while under complete recycling, it is observed to follow an inverted U-shaped relationship with the recycling rate. These findings are seen to contribute to the environmental and industrial economics literature by clarifying how recycling efficiency and cost structures shape optimal extraction strategies, offering insights for sustainable resource management and circular economy policies.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".