Walking the Talk: Establishing Best Practices for Attributing and Licensing Employee-Created Works
Bibliographic record
Abstract
Library employees routinely create content that is subject to copyright, ranging from web pages to video tutorials to photographs to social media posts. In most cases these contributions are invisible, as the creativity and intellectual effort of employee creators is typically unacknowledged. At the University of Guelph, we endeavoured to bring the works of employees into the spotlight by providing attribution on public-facing content whenever possible, while also facilitating downstream uses of those works through the use of open licenses. In doing so, we hoped to address a general lack of awareness and understanding of copyright and model respectful copyright practices for library employees and users alike. However, establishing and implementing these new copyright-focused practices was not without challenge and controversy. This paper – which builds upon a presentation we delivered at the 2024 ABC Copyright Conference (Martin & Versluis, 2024) – explores the obstacles we encountered in our multi-year journey to develop practices that were acceptable to content creators and content managers, while also respecting the boundaries of institutional intellectual property policies and collective agreements. Keywords: copyright literacy, staff development, copyright ownership, employee created works, library policy and documentation
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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 | 0.002 | 0.005 |
| 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 | 0.003 | 0.008 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".