Bringing the idea of the environment to law: a comparative study of early environmental law textbooks
Bibliographic record
Abstract
Abstract From 1948 to 1972 the idea of the environment gained solidity within the sciences and in global politics, as a thing or a concept, which spoke of a need to save humanity from the harms it was inflicting on the natural world. As historians Warde, Robin and Sörlin explain, the idea brought about a revolution in the sciences, casting scientists as environmental problem solvers, fundamentally changing the way they worked. In this paper we connect law and lawyers to this history. We ask, did lawyers contribute new meanings to the idea of the environment when they first presented laws and parts of legal practice as ‘environmental’? Were they mere translators of the scientists’ ideas? And did they envisage the emergence of new environmental legal experts, who might change legal culture? We examine the early environmental law textbooks in five countries (Australia, Canada, England, New Zealand and the US) and devise ideal types to explain the associations, values and choices which underpinned their presentation of the ideas of ‘the environment’, ‘environmental law’ and ‘environmental law expert’. We consider that these types are useful conceptual tools which raise ongoing questions about the relationship between environmental law and its broader context.
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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 | 0.008 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.013 | 0.018 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".