Beyond Zero Waste Concept: A Revolution for Sustainable Community
Bibliographic record
Abstract
A community reflects a big number of citizens grouped in an area, sharing common characteristics, traditions, lifestyle and daily needs. People within a community will affect the area and surrounding citizens as per their daily acts and traditions as well as being affected by the surrounded environment too; meaning that the community and the people living within are interconnected where the action of one end will lead to a reaction in the other. Thus there is a need to introduce the concept of sustainable communities, which focuses on water, air quality, wastes, energy and materials being more of a marketing word nowadays to companies, industries, governments and communities. However, since natural resources are being abused to a big extend that currently some living categories cannot access. This leads to widening the gap between the rich and the poor thus diversifying the community. In addition to, negative actions are impacting the surrounding environment leading to an undesired living standards and lifestyle like the accumulation of wastes and the consequent rise of diseases and pollution. In brief, the objective of this paper is to propose a zero waste practical approach for urban communities, hoping to reach a common ground of understanding. While also having defined set of actions towards having a balanced environment and ecosystem for a better, balance, pollution-free life and natural resources management for future generations’ needs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.026 |
| Scholarly communication | 0.009 | 0.015 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".