What Happened After the 2012 Shift in Canadian Copyright Law? An Updated Survey on How Copyright is Managed across Canadian Universities
Bibliographic record
Abstract
Abstract Objective – The purpose of this study is to understand the practices and approaches followed by Canadian universities in copyright education, permissions clearance, and policy development in light of major changes to Canadian copyright law that occurred in mid-2012. The study also seeks to identify aspects of copyright management perceived by the universities to be challenging. Methods – In 2015, an invitation to complete an online survey on institutional copyright practices was sent to the senior administrator at member libraries of Canada’s four regional academic library consortia. The invitation requested completion of the survey by the person best suited to respond on behalf of the institution. Study methods were largely adapted from those used in a 2008 survey conducted by another researcher who targeted members of same library consortia. Results – While the university library maintained its leadership role in copyright matters across the institution, the majority of responding institutions had delegated responsibility for copyright to a position or office explicitly labeled copyright. In contrast, respondents to the 2008 survey most often held the position of senior library administrator. Blanket licensing was an accepted approach to managing copyright across Canadian universities in 2008, but by 2015 it had become a live issue, with roughly half of the respondents indicating their institutions had terminated or were planning to terminate their blanket license. Conclusion – In just seven years we have witnessed a significant increase in specialized attention paid to copyright on Canadian university campuses and in the breadth of resources dedicated to helping the university community understand, comply with, and exercise various provisions under Canadian copyright law, which include rights for creators and users.
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 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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".