THE KNOWLEDGE, ATTITUDE AND PRACTICE TOWARDS SOLID WASTE MANAGEMENT AMONG MOGADISHU RESIDENTS - SOMALIA
Bibliographic record
Abstract
This research we proposed the knowledge, attitude and practice towards solid waste management among Mogadishu residents – Somalia. Solid waste management is one of the major challenges faced by many countries around the globe. Inadequate collection, recycling or treatment and uncontrolled disposal of waste in dumps can lead to severe hazards, such as health risks and environmental pollution. Similarly there is problem in Africa. Africa is facing a growing waste management crisis. While the volumes of waste generated in Africa are relatively small, compared to developed regions, the mismanagement of waste in Africa is already impacting human and environmental health. Specially in Somalia show that solid waste management is a growing crisis that engulfs all urban centers within the country, because of a turbulent history, especially over the last quarter century. The purpose of this study is to assess the knowledge, attitude, and practice of recycling solid waste management in Banadir region, Mogadishu – Somalia. However, this study is used quantitative approach conducted in Shebelle campus, Km4 campus and Gaheyr campus in Mogadishu Somalia. The numbers of students in all faculties from batch five to batch eight are 4,467 Students and the sample size will be 367. Findings of the study Knowledge level of the Majority of respondent 330 (89.2%) were have knowledge. While the most respondents 134 (36.5%) were finding over TV. The relationship between the knowledge, attitude and practice was significantly positive as the respondents majorities have said. This study is significant for staff and students by Increasing their safety and health, Reducing and eliminating adverse impacts of solid waste materials on human health and the environment surrounded. Finally recommend to be aware that improper waste disposal is a threat to 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".