Copyright Consultations Submission
Bibliographic record
Abstract
The entertainment software industry is one of the fastest growing market segment in the global economy, with Canada rapidly establishing itself as a world leader in the multi-billion dollar global video game industry. The employment opportunities in this industry, as well as its investments in research and technology are also significant. These investments are not without risk – in the highly competitive industry of video game production the chance of a video game being a commercial failure outweighs the chances of its success. Internet piracy of video game software has also undergone explosive growth and represents a significant problem for the entertainment software industry. Video game piracy drastically reduces the industry's capacity to sustain the enormously high creative costs associated with video game production, potentially leading to lost revenue, lost jobs, or worse. In an effort to protect their products from piracy, the video game industry has implemented various measures, including technological protection measures and other copy protection techniques, yet such measures are not fail-safe and are subject to circumvention. Compounding this problem, copyright law in Canada does not provide sufficient protection. Consequently, the Entertainment Software Association of Canada herein presents ways in which Canadian legislators can use copyright law to reduce piracy. Modernizing copyright law will, in turn, allow for a fair and vibrant marketplace and, in so doing, enhance both Canada‘s competitiveness and the public interest.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.018 | 0.008 |
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; both teacher heads agree on what is shown here.
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".