Bibliographic record
Abstract
Law is forbidding, correcting, punishing, helping, restoring, rewarding. Law needs tools, of other disciplines too. Language [of law too] is a means of communication and of isolation (wanted or imposed). Expressing law, interpreting law, implementing law, exploiting law needs all sorts of language. Law and economics discover and uncover rational (though still often irrational) choices. Judicial decisions are political decisions, critical legal studies point out. Law is always influenced by politics. Politics can be benefactor and destructor. Rituals as expressions of living law may have double (or multiple) meaning. Law is always influenced by religion – either explicitly or implicitly. Convivencia in the same country of people of different religions and, accordingly, application of different laws of civil status (for example in Liban, in Greece, etc.) is a fact. First nations (in Latin America, USA, Canada, Australia, New Zealand, Caribbean, etc.) live together (not really, not always in an idoneous way) with former colonizers and immigrants. Is there a real Convivencia of laws, there (as most countries in Africa have almost managed to achieve), or primacy of one (central) law and exclusion of the others? In many countries, there are different rules for the same issues, according to the particular problems of the persons to whom they apply – hypothetically aiming at the same protection(?). Is it an opposite discrimination or just a means of organizing the way to live together? Co-existence, Com-petition, Com-paring, Con-vivencia: Harmony is feasible, is possible, is not alchemy, it respects and requires the different, in order to be a rich image of life.
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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.012 | 0.052 |
| Scholarly communication | 0.016 | 0.018 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.019 | 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; 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".