The Law's Critical Role in Developing Human-Environment Relationships after COVID-19 Pandemic (A Study of Ecofeminism)
Bibliographic record
Abstract
The relationship between humans and the environment has managed to evolve throughout history. This relationship can be seen in both how people interact with nature and in the environmental laws they pass. These two things demonstrate how humans rule the environment. The COVID-19 pandemic has become one of the catalysts for rethinking the human-nature relationship and the impact of human dominance on the environment. Ecofeminism has emerged as a viable theory for combating this dominance. The historical development of environmental law as well as ecofeminism studies on the significance of environmental law will be examined in this study. This research is historically and philosophically oriented normative and qualitative jurisprudential research. The findings show that environmental law has developed over time in three distinct periods: traditional, modern, and post-modern. Three laws have been used to address environmental issues throughout Indonesia's history of environmental law development. Despite government efforts to uphold the framework of environmental law based on the idea of anthropocentrism, there are global environmental problems. The study of Ecofeminism and the urgent need for environmental laws that emphasize balance and combat human dominance of the environment must be built upon after the COVID-19 Pandemic. According to Ecofeminism, every legislature must establish this human-environmental relationship in order to end human dominance that endangers the environment.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.048 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".