Intensity of Citizens’ Perception and Behavior Towards Electronic Waste Management (A Case Study, Qom city)
Bibliographic record
Abstract
Background: The growing use of electrical and electronic equipment in recent decades has generated a noticeable volume of electronic waste (e-waste), posing a major global environmental challenge. Therefore, the current study investigated household electronic waste management behaviors among citizens of Qom province, Iran. Methods: The data for this cross-sectional analytical study were collected via a validated questionnaire from 384 citizens visiting recycling centers in Qom. Subsequent analysis was performed using Excel and SPSS software. Results: The was found that only 37% of the respondents perceived the severe environmental consequences of e-waste. In contrast, the majority (93%) were aware of the direct economic benefits of recycling, while 41% recognized the indirect economic benefits. Regarding management behaviors, repair and reuse were the most common strategies (reported by 45% to 94% of the respondents), whereas delivering waste to official recycling centers was the least common (less than 5%) Conclusion: A lack of awareness regarding the environmental consequences of e-waste reduces its separation rate. Thus, decision-makers should incorporate the economic incentives that promote the sale and reuse of electronic equipment into e-waste management plans.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".