Bibliographic record
Abstract
The purpose of this report is to provide cost of capital formulae for assessing the effects of taxation on the incentive to invest in oil and gas industries in Canada. The analysis is based on the assumption that businesses invest in capital until the after-tax rate of return on capital is equal to the tax-adjusted cost of capital. The cost of capital in absence of taxation is the inflation-adjusted cost of finance. The after-tax rate of return on capital is the annualized profit earned on a project net of the taxes paid by the businesses. For this purpose, we include corporate income, sales and other capital-related taxes as applied to oil and gas investments. For oil and gas taxation, it is necessary to account for royalties in a special way. Royalties are payment made by businesses for the right to extract oil and gas from land owned by the property holder. The land is owned by the province so the royalties are a rental payment for the benefit received from extracting the product from provincial lands. Thus, provincial royalty payments are a cost to oil and gas companies for using public property. However, since the provincial government is responsible for the royalty regime and could use taxes like the corporate income tax to extract revenue, one might think of royalties as part of the overall fiscal regime to raise revenue. In principle, one should subtract the rental benefit received from oil and gas businesses from taxes and royalty payments to assess the overall fiscal impact. This is impossible to do without measuring some explicit rental rate for use of provincial property. Further, royalty payments may distort economic decisions unlike a payment based on the economic rents earned on oil and gas projects. Instead, for comparability across jurisdictions, one might calculate the aggregate tax and royalty effective tax rates (such as between Alberta and Texas).
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".