Bibliographic record
Abstract
Abstract. Early exhaustible resource economics provides an important foundation for recent suggestions that firm‐level economic modeling plays a larger role in the analysis of resource scarcity. The lack of empirical support for Hotelling’s r‐percent rule, introduced in 1931, and recent suggestions that industry behavior may not be reducible to firm behaviors are the primary motivating factors for examining the relative value of Gray’s contribution to the field of exhaustible resource economics relative to Hotelling’s contribution. Specifically, Gray’s papers that appeared in the 1910s provide insight into the heterogeneity of deposits and their spatial dimensions, and offer the possibility that firms will be subject to fixed costs carried over between periods. In this paper, the arguments presented by Gray are formalized in a dynamic model, which allows the differences between Gray’s and Hotelling’s assumptions to be more fully explored. The results of the paper illustrate that by considering spatially identifiable heterogeneous deposits, fixed costs, and entry costs, in general Hotelling’s r‐percent rule is not a sufficient condition for firm‐level decision making and that firms’ extraction behavior cannot be linearly aggregated to describe industry behavior.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".