Why this work is in the frame
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Bibliographic record
Abstract
In this paper the Hotelling model of exhaustible resource extraction is extended to incorporate network externalities. The impact of network externalities on competition between an exhaustible resource and a renewable resource sector is studied. The motivation for the paper is that the benefits to consumers from consumption of fossil fuels versus renewable energy sources depend on the number of other consumers consuming the same type of energy. For example purchase of fossil fuel driven vehicles has greater benefits if there are large numbers of other drivers of such vehicles resulting in a large network of infrastructure for the technology, e.g. roads, gas stations, automobile clubs. Likewise purchase of electric or solar- hydrogen vehicles would have increased benefits if there were a large number of other users of such vehicles with a large infrastructure network available such as plug-in points for electric vehicles of refuelling stations for hydrogen vehicles. The paper examines the transition from a fossil fuel economy to a renewable energy economy with network externalities within the framework of a differential game between the policymaker who determines the extent of extraction of fossil fuels and consumers who choose between a fossil fuel network and a renewable energy network in response to network externalities in consumption. Two cases are considered one with two immature industries both characterised by network externalities and one with a mature fossil energy sector in which network externalities are absent and an immature renewable sector that is characterised by network externalities. The key results demonstrate that network effects will have different impacts when technological choices are between two immature sectors as opposed to choices between a mature and an immature sector. In the latter case network externalities are a key barrier whereas in the former the impact depends on the remaining lifetime of the fossil energy source. The results also have implications for policy in particular it is suggested that barriers to the transition to renewable energy are a more appropriate target for policy than attempting to reduce the costs of capturing renewable energy as the latter is likely strengthen the marginal impact of network externalities on resource extraction thereby slowing the transition to renewable energy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 it