A Survey on Understanding the Perception and Awareness Towards a Circular Economy: A Comparative Study Between Nepal and the USA
Bibliographic record
Abstract
This article offers a comparative analysis of the perception and awareness people have concerning the circular economy (CE) in Nepal and the United States of America (USA). The survey in the form of online questionnaires were distributed through convenience sampling and data was collected from 29 respondents in Nepal and 25 in the USA. The results indicate that, across the sampled countries, though respondents were highly concerned about the environment and resources utilization, their perception and understanding of CE principals and its applicability were limited to the concept of reuse, recycle and remanufacture (3R). Similarly, organizational involvement in CE activities were found to be significantly low in both countries, indicating no structural or operational level support such as creating job positions for CE officers. Additionally, the practice of publishing sustainability and circularity reports to enable the CE were not found during the data analysis procedure. In comparison to Nepal, USA respondents picked inter and intra organizational collaboration and cooperation along with research and development (R&D) as an important enabler of CE. Finally, policy level interventions through mandatory and voluntary regulations, subsidization of CE activities and involvement of governmental and non-governmental agencies were recommended in creating a positive perception and awareness of CE. Keywords: Circular economy, comparative study, awareness, perception
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".