Converting Technology to Mitigate Environmental Damage
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There are many situations where policy makers would like to induce firms to make a major discrete conversion in production technology to help the environment. This paper examines how heterogeneity in the operating condition of firms' plant and equipment, which cannot be observed by policy makers, can affect the choice between incentives to encourage conversion to a cleaner technology. By relating different conditions of firms' plant and equipment to production costs, extent of environmental damage, and cost of conversion to a cleaner technology, we show when a perfectly discriminating incentive to encourage conversion is not feasible. In addition, we show that firms with plant and equipment in better condition will convert their technology to mitigate their environmental damage, and firms with plant and equipment in poorer condition will not. This and a series of additional results lead to conditions under which an administratively simple uniform lump-sum incentive to switch to cleaner technology is preferable to one based on output. These results and conditions extend to cases where there are network externalities in conversion, and where there is strategic timing in firms' choice of when to convert.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.004 |
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