Animals in world society: Constitutional and legislative incorporation, 1972–2020
Bibliographic record
Abstract
This article analyzes cross-national and longitudinal variations in the incorporation of nonhuman animals into country constitutions and legislation. We argue that incorporation follows from the scientific rationalization and human rights-based ontological elaboration of nonhuman animals in world society, carried by a growing number of intergovernmental agreements and international nongovernmental organizations (INGOs). To test our ideas, we use event-history analyses on original data from 195 countries for the period 1972–2020. The models of constitutional incorporation show mixed results, with positive effects from human rights and INGOs but negative effects from science and intergovernmental agreements. The models of legislative incorporation show consistent positive effects from world factors, even when controlling for a range of domestic factors. Legal incorporation suggests an extension of the boundaries of “society,” driven by the rising prominence of highly rationalized and elaborated models of nonhuman animals, replete with dignity, sentience, and even tentative forms of rights and personhood.
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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 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".