IT’S A HARD KNOCK LIFE: A CRITIQUE OF THE LEGISLATIVE RESPONSE TO THE ORPHAN WORKS PROBLEM IN THE UK
Bibliographic record
Abstract
This article serves to identify the flaws in the three-pronged solution to the orphan works problem implemented in the UK. It concurrently questions the compatibility of the UK’s approach with the objectives sought to be achieved by the legislation; namely to ensure legal certainty with respect to the use of orphan works, to facilitate cross-border access to orphan works, to facilitate mass digitisation projects and to ensure that authors’ moral rights remain respected and protected. In addressing these issues, the article seeks to highlight aspects of the UK solution which could be amended in order to ensure that copyright law remains relevant and workable in the digital age, whilst maintaining a fair balance between protecting the interests of right holders and the public.
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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 | 0.027 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.019 | 0.063 |
| Scholarly communication | 0.023 | 0.014 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.036 | 0.024 |
| Insufficient payload (model declined to judge) | 0.006 | 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".