Improving Urban Residents’ Awareness of the Impact of Household Activities on Climate Change in Lagos State, Nigeria
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Climate change is much discussed among professionals, academics, governments, local and international organisations. It is a phenomenon that is increasingly gaining attention because of its negative impacts on human, and natural environments and the economy. Human activities exacerbate climate change and this in turn impacts on livelihood and environment. Urban activities such as transportation and building (household) related activities increase atmospheric concentration of greenhouse gases. Other activities that contribute to greenhouse gas emission include change of land use, removal of land cover, use of fertilizer, pollution of water bodies, deforestation, industrialization, urbanization and poor municipal waste management. However, it is quite unclear whether urban residents have adequate awareness and understanding of what the phenomenon entails and how their daily activities impact atmospheric greenhouse gases’ concentration. To this end, questionnaires were distributed to 600 households selected from three local government areas in Lagos State. Data gathered were analysed and presented using tables, percentages, pie and multiple bar charts. Result of analysis indicate that although most urban residents indicate various level of awareness of occurrence, they are least aware of the contribution of household activities to atmospheric greenhouse gas concentration and that professional property managers hardly sensitize occupants in this direction. The study concludes by suggesting ways to call the attention of urban residents to the impact of household activities on atmospheric greenhouse gases’ concentration with a view to reducing emission from this sector in the future.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it