What Canadian Archivists Know About Copyright and Where They Get Their Knowledge
Bibliographic record
Abstract
This article reports the findings of a study which investigated the sources of Canadian archivists’ knowledge of copyright and the quality of their knowledge in terms of the extent to which it is accurate and up-to-date. The study found that Canadian archivists obtain their copyright knowledge from a variety of sources, not all of which are authoritative or current; as a result, the quality of their knowledge varies greatly. Some appear to have a good understanding of copyright, others misunderstand certain aspects in ways that have consequences for access and use, or that may put the repository in a position of infringing copyright, albeit unintentionally. The article concludes with recommendations to address weaknesses in how practitioners learn about copyright and keep their knowledge current. RÉSUMÉ Cet article présente les résultats d’une étude qui a été menée afin de déterminer les sources du savoir des archivistes canadiens en matière du droit d’auteur et de mesurer la qualité de ces renseignements. L’étude montre que les archivistes canadiens obtiennent leurs renseignements par rapport au droit d’auteur à partir d’une variété de sources qui ne sont pas nécessairement sûres ni à jour; par conséquent, la qualité de leurs connaissances varie énormément. Certains semblent avoir une bonne connaissance du droit d’auteur tandis que d’autres comprennent mal certains aspects, ce qui peut avoir des conséquences néfastes sur l’accès et l’utilisation, ou mener un centre d’archives à ne pas respecter le droit d’auteur, quoique de façon involontaire. Cet article conclut en fournissant des recommandations pour assurer que les praticiens aient et conservent une bonne connaissance du droit d’auteur.
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 | 0.016 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.015 | 0.015 |
| Science and technology studies | 0.029 | 0.015 |
| Scholarly communication | 0.021 | 0.010 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".