Bibliographic record
Abstract
Copyright industries are an important part of the economy, accounting for five to over ten percent of the GDP of certain economies. Studies suggest that the copyright sector has grown faster than the entire economy in most countries. However, the author’s earlier study found that Canada’s core copyright-based industries accounted for a smaller share of the economy when compared to those industries in the United States and Europe. This paper examines the factors behind the slower growth of copyright-based industries in Canada. In particular, the paper estimates the growth of the main economic indicators of the core copyright-based industries of Canada and compares them with those of the rest of the economy and with those of the copyright-based industries in the United States. The study also explores the impacts of factors such as exports, foreign direct investment, and information and communication technologies on the productivity of the copyright-based industries. Generalized Method of Moments (GMM) and System GMM methods are used to estimate the models. The study suggests that there is a significant gap between Canada and the United States in terms of value added, employment, investment, and labor productivity growth of core copyright-based industries.
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How this classification was reachedexpand
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".