Bibliographic record
Abstract
This paper examines the necessity to embrace and adopt environmental education. Essentially, environmental education has to do with the creation of awareness and spread of knowledge and understanding about the environment and environmental challenges. Fundamentally, it deals with decision making about environmental actions. Hence, it engages in actions to improve and sustain the environment. Environmental education is about good governance. It is highly indispensable. It is required in solving environmental problems with unimaginable consequences. On this note, the salient issues addressed in this paper are human-environment interaction, environmental awareness, environmental literacy, and sustainability. The reviewed literature revealed that the level of environmental education in developed countries of the world is far higher than that of the developing countries. To this end, this study recommends that the developing countries should move with the tide in terms of environmental education. They should attach more value to the environment. Moreover, they should promote responsible behavior towards the environment. Above all, individuals, institutions the government, non-governmental organizations, as well as community-based organizations should be involved in environmental education.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".