Subsidy strategy for reserving flexible capacity of emergency supply production
Why this work is in the frame
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Bibliographic record
Abstract
Abstract This paper investigates a government's subsidy strategy for motivating a manufacturer to set up a flexible production line for emergency supplies. Four subsidy strategies are proposed to ensure a desired service level in case of an emergency: zero subsidy, a fixed subsidy, a marginal subsidy, and a hybrid subsidy. We develop a game theoretical model to examine how the government can induce a manufacturer to set up a flexible production line that can respond promptly to an emergency, based on the manufacturer's cost structure (fixed and marginal costs). We find that when the marginal profit of an emergency product is higher than that of the manufacturer's regular product, a fixed (marginal) subsidy is the dominant strategy if the manufacturer's fixed (marginal) cost is high, while a hybrid subsidy strategy is dominant if both costs are high. When the marginal profit of an emergency product is lower than that of the manufacturer's regular product, neither a fixed subsidy nor a zero subsidy will be the dominant strategy. We also find that a marginal subsidy can ensure the effectiveness of the strategy, while a fixed subsidy helps improve strategy efficiency. We use government subsidy strategies implemented for Chinese COVID‐19 emergency supplies as examples to demonstrate the effectiveness and efficiency of the subsidy strategies under the proposed framework. We also extend the discussion by considering the manufacturer's social consciousness.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it