Strategies for Climate Hope and Sustainable Water Management
Bibliographic record
Abstract
Water is the foundation of everything that lives.However, the persistent problems of flood, drought, fluctuating precipitation and changes in weather conditions clearly attest to an emerging crisis in water management.This study employs a positivist epistemological positioning approach to capture the views/opinions of stakeholders in the geo-political zones of Nigeria on the causes and effects of climate change, and strategies for climate hope and sustainable water management.In all, 240 survey questionnaires were administered to the randomly selected samples of stakeholders i. e. public authorities, business and industry, non-governmental organisations, workers and trade unions, scientific and technological community, indigenous people, children and youth.Of these, 210 completed and usable questionnaires (representing 87.5% response) were retrieved.Secondary data were collected through a systematic review of relevant scholarly publications.Descriptive statistical (Relative Importance Index, RII) tool was used along with SPSS version 28 for primary data analysis.Findings of the study uncovered 'carbon emissions' and 'rise in global temperature' as the major cause and effect of climate change respectively.Therefore, this study strongly advocates 'net-zero emissions' and 'water reuse' as ultimate strategies for climate hope and sustainable water management.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".