Bibliographic record
Abstract
In this article we use four Canadian Supreme Court decisions that have substantively contributed to the constitutional recognition of aboriginal rights to assess the impact that changes in the security of commercial property rights have had on long‐run macroeconomic performance. We use a series of event studies to measure the extent to which each court decision had an effect on the common share prices of Canadian forestry firms. These share price effects reflect investors' perception of the decisions' impact on forestry firms' contemporaneous access to resource stocks and uncertainty surrounding the security of their access into the future. A simulation model based on a resource industry's dynamic optimization problem links the stock access and uncertainty effects implied by our event studies to the commercial producers' economic fundamentals. Changes in the resource industry's simulated profits can be used in a general equilibrium framework to estimate the effect that the Court's decisions had on Canadian real GDP per capita growth during the 1970–2005 period. Our methodological approach allows us to estimate the aggregate, long‐run macroeconomic effects that resulted from the Court's recognition of aboriginal rights, and also trace the channels through which these changes in the distribution of property rights influenced performance; we assess the relative importance of the current access and future uncertainty components of these changes.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".