Bibliographic record
Abstract
The Constitution of India through an amendment of 1976 prescribes a Fundamental Duty ‘to have compassion for living creatures’. The use of this notion in actual legal practice, gathered from various judgments, provides a glimpse of the current debates in India that address the relationships between humans and animals. Judgments explicitly mentioning ‘compassion’ cover diverse issues, concerning stray dogs, trespassing cattle, birds in cages, bull races, cart-horses, animal sacrifice, etc. They often juxtapose a discourse on compassion as an emotional and moral attitude, and a discourse about legal rights, essentially the right not to suffer unnecessary pain at the hands of humans (according to formulae that bear the imprint of British utilitarianism). In these judgments, various religious founding figures such as the Buddha, Mahavira, etc., are paid due tribute, perhaps not so much in reference to their religion, but rather as historical icons—on the same footing as Mahatma Gandhi—of an idealized intrinsic Indian compassion.
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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.042 |
| Scholarly communication | 0.017 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.008 | 0.010 |
| 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".