Bibliographic record
Abstract
The rules governing the ownership of wild animals are of ancient origin. In essence, title is based on first occupancy. However, the rights acquired by occupancy are qualified: where the animal escapes, title is lost. As a corollary, the killing of the animal renders title absolute. These principles have been applied in a variety of contexts. However, the law governing capture within the Newfoundland seal fishery seems to have veered off on a different course. This article explores the Newfoundland jurisprudence on the ‘law of capture’ as manifested in a cluster of decisions rendered by the Supreme Court of Newfoundland in the latter part of the nineteenth century. The principles articulated in these cases are inconsistent inter se. The guiding doctrines were seemingly in transition and contested. This article seeks to discern why these disputes emerged – and the governing principles called into question – long after the commencement of the seal hunt itself. Moreover, the differing judicial approaches reflect the penchant of the Newfoundland judiciary to adopt unique legal doctrines in response to the special needs of the colony. The malleability of the legal concept of ‘possession’ aided that judicial activism. These themes will be explored.
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 | 0.001 | 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 | 0.010 | 0.012 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".