Bibliographic record
Abstract
This article examines the ways in which American archival repositories attempt to control further uses of their online content, their reasons for doing so, and the role of copyright in such practices. In a study based on 96 repository websites, 66 survey responses, and 18 interviews with staff, the data revealed that institutions use technical measures to limit image quality or prevent copying and also establish terms and conditions that govern further uses. In some cases, a repository may be protecting its legitimate copyright interests, but in most other cases the repository is not a rights holder. Unfortunately, conditions placed on further uses are often linked to copyright, even though controls are intended to ensure attribution, generate revenue, or track use. Archives should re-examine their policies on reuse of holdings to make sure they are not invoking copyright in ways that present a barrier to the use of online documentary heritage. RÉSUMÉ Cet article examine les façons dont les centres d’archives américains tentent de contrôler davantage l’utilisation de leur contenu en ligne, les raisons pour ce faire et le rôle du droit d’auteur dans cette pratique. Dans une étude basée sur 96 sites web de centres d’archives, 66 réponses à un sondage et 18 entrevues avec du personnel, les données révèlent que les institutions se servent de mesures techniques pour limiter la qualité des images ou prévenir le copiage et établissent aussi des conditions qui régissent les autres utilisations. Dans certains cas, les centres d’archives peuvent agir pour protéger leur légitime droit d’auteur, mais dans la plupart des cas, les centres d’archives ne sont pas les détenteurs de ce droit. Malheureusement, les conditions d’utilisation mises en place sont souvent liées au droit d’auteur, même si l’intention des moyens de contrôle est d’assurer l’attribution, de générer des revenus ou de garder trace de l’utilisation. Les centres d’archives devraient réexaminer leurs politiques sur la réutilisation de leurs fonds et collections afin de s’assurer qu’ils n’évoquent pas le droit d’auteur de sorte à restreindre l’utilisation du patrimoine documentaire en ligne.
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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 | 0.006 | 0.066 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".