Animals: ‘objects’ or ‘sentient beings’? A comparative perspective of the South African law
Bibliographic record
Abstract
This paper provides a comparison of the law related to the classification of animals as either "legal objects" or "sentient beings" and "non-human persons." In this paper, the definition of "objects" in the South African Law of Persons will be explored. An explanation of the difference between a legal "object" and a legal "subject" in South African law will be provided. Legal research is done with the focus being Interpretative Research. In order to understand the classification of animals in South African law, the relevant provisions of the Animal Protection Act 71 of 1962 and the Performing Animals Protection Act 24 of 1935 (as amended) will be explained. Secondly, the classification of animals in the law of other countries will be explored. Examples will include France, where the legal status of animals has changed from that of "personal property" to "sentient beings"; New Zealand, where the Animal Welfare Amendment Act 2 of 2015 recognizes animals as sentient beings; the legal reforms in Quebec, Canada, stating that animals are not objects and the declaration by India that Cetaceans are "non-human persons." Implications of this research for practice may include a reclassification of animals as persons, which would result in the need for changes to be made in South African law. In conclusion, suggestions are made about whether the classification of animals as "objects" in South African law should be revised.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".