Bibliographic record
Abstract
In recent years a set of challenging questions have arisen in relation to the status of animals; their treatment by human beings; their cognitive abilities; and the nature of their feelings, emotions, and capacity for suffering. This ground-breaking book draws from integrational semiology to investigate arguments around the rights of certain animals to be recognized as legal persons, thereby granting them many of the protections enjoyed by humans. \n \nIn parallel with these debates, the question of the legal personality of artificial intelligence (AI) systems has moved to the forefront of legal debate, with entities such as robots, cyborgs, self-driving cars, and genetically engineered beings under consideration. Integrationism offers a framework within which the wider theoretical and practical issues can be understood. Law requires closure and categorical answers; integrationism is an open-ended form of inquiry that is seen as removed from particular controversies. This book argues that the two domains can be brought together in a challenging and productive synthesis. A much-needed resource to examine the heart of this fascinating debate and a must-read for anyone interested in semiology, linguistics, philosophy, ethics, and law. \n \nThe Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.008 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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; both teacher heads agree on what is shown here.
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".