Law and energy interaction in light of interdisciplinary studies
Bibliographic record
Abstract
With due attention to growing need of countries for energy resources, new and diverse topics in the field of law and energy have been designed that strengthen extensive interdisciplinary studies and researches in this field. The legal dimension of the exploitation of energy types, including the protection of the environment, foreign investment, and the creation of legal mechanism at domestic and international levels, energy security, and other issues of countries necessitates interdisciplinary studies and the publication of legal researches related to energy substantially. Energy Law is one of the interdisciplinary majors that have been taken into consideration in faculties of several countries, including Australia, England, the United States, and Canada. The fact that Energy Law as a major can itself be under other specialized courses which increase its value as an academic field and it can be said that the establishment of "Energy Law" as an interdisciplinary major, considering its scope and content in the curriculum of the faculty of law of other countries, including Iran, is undeniable. This article tries to provide an appropriate context for energy law as an interdisciplinary major to the students of law and other related disciplines. For this purpose, in addition to explaining the concept, characteristics and status of energy, we will examine the principles, elements and levels of this major.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.041 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| 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".