Section 30.1 and Software Collections: A Users Guide
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
Like fair dealing (Section 29), Section 30.1 of the Copyright Act, known as the “Management and maintenance of collection” exception, places certain software preservation activities by libraries, archives, and museums (LAMs) outside the scope of copyright. Section 30.1 is similar to fair dealing in that it allows LAMs to engage in software preservation activities without permission from rightsholders. Unlike fair dealing, which the Supreme Court of Canada has defined as a broad and flexible user’s right that could apply to a wide variety of uses, [see paragraphs 30-32 of Theberge and paragraph 48 of CCH) the rights granted by Section 30.1 apply to preservation activities directly and have statutorily specified eligibility requirements, limitations, and procedures. Nevertheless, it is important to understand the baseline that Section 30.1 provides to LAMs engaging in the preservation of software. Section 30.1 identifies types of lawful copying that do not require permission from rightsholders. The activities that 30.1 permits do not encompass all copying that may be necessary to preserve and maintain access to software collections, and are subject to limitation. Therefore, it is advisable to read this guide alongside SPN’s Best Practices for Fair Use in Software Preservation, the situations, principles and limitations of which are transferable into the Canadian context of fair dealing.
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 | 0.001 | 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 | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 it