Did royalties really impact on profits to the extent that coal companies believed? A case study of the Denbighshire Coalfield, 1870–1914
Bibliographic record
Abstract
During the last quarter of the nineteenth century coal companies in the UK became increasingly vocal in their condemnation of the royalty rates charged by the mineral owners of the UK. Such was the furore that a Royal Commission on Mining Royalties was set up in 1890 with a remit to investigate these concerns. However, the commission concluded that royalties were not unduly harsh and did not make up a disproportionate part of costs. This article is an attempt to establish whether the views of the coal companies had any basis in fact or whether, as Mitchell asserts, ‘royalties formed a comparatively unimportant fraction of the total cost of the coal industry in the nineteenth century’ (B.R. Mitchell, (1984), The economic development of the British coal industry 1800–1914, Cambridge: Cambridge University Press, p. 256). We start by considering royalties within a UK context and the issues that affected the methods used and the rates set. We then examine how royalties affected the profits per ton of the coal companies in Denbighshire for which archival records survive. This will enable us to determine whether Mitchell's view was correct or whether, as Fine believes, the impact can only be determined by considering the marginal impact of royalties on profits.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".