Language and Discourse in the Canadian Copyright Act Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study has examined the 2017-2019 Parliamentary review of Canada’s Copyright Act by the Industry, Science, and Technology (INDU) Committee, focusing on the impact the discourse around copyright in Canada has on legislative change. We have investigated the recommendations for amendments to the Copyright Act, and the rationales put forward to support them, made to the INDU Committee by various types of stakeholders, as well as the interactions between stakeholders and committee members in their meetings. We aimed to make connections between these contributions and the committee’s own resulting report and recommendations, as well as with any responses or actions taken by the federal government. Our primary focus has been on areas of discussion and debate relevant to higher education, including fair dealing, collective licensing in Canada, Indigenous rights, Crown copyright, technological protection measures, and contract override of user rights. We have a particular interest in using our findings to support future advocacy for copyright and user rights in higher education and libraries. See the Wiki for our publications and presentations. A number of our data files and codebooks are available below. Co-Investigators: Jennifer Zerkee, Copyright Specialist, Simon Fraser University; Stephanie Savage, Scholarly Communications and Copyright Services Librarian, University of British Columbia Research Assistants: Arianna Alcaraz (University of Alberta School of Library and Information Studies) 2023-2024; Will Power-Jenkins (University of Toronto iSchool) 2022-2023; Jentry Campbell (UBC iSchool) 2020-2021; Jessi Robinson (UBC iSchool) 2021 This project has received funding from an SFU/SSHRC Small Explore Grant (2022) and a CARL Research in Librarianship Grant (2020).
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.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.300 | 0.352 |
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 it