It has not always been like this: public opinion of climate change in Port Harcourt, Nigeria
Bibliographic record
Abstract
Climate change is affecting weather and climate extremes globally. It has been a subject of debate and controversy leading to the emergence of climate deniers and skeptics. It is a subject of great relevance because of its wide-ranging impacts on socioeconomic and natural systems. This necessitates long-term strategic decisions and response measures. There is a gap between the general public and the scientific community in terms of their awareness, understanding, and perception of climate change. Responding to the global climate crisis requires different actions at various levels, including individual. However, the manner in which the public and societies at large act in response to climate change is dependent on their perceptions and beliefs of climate change. This makes understanding the common opinion on climate change salient. There is an overrepresentation of climate change public opinion research in western nations in comparison with developing countries. This work thus contributes to filling this gap by engaging with members of the public who experience flooding in Nigeria to understand their perceptions and opinions on climate change. Qualitative research was carried out with focus group interviews and semistructured one-on-one interviews as primary data collection tools. The research findings indicate that there is a consensus that climate change is occurring, as evidenced by changes in weather patterns over the years. However, there were differences in opinion among the participants on how it was presenting. This work thus yields key insights on the level of awareness of the climate phenomena in a developing African city. Knowledge of climate change can encourage the public to engage more with the climate crisis, act in their own way, and even mobilize to influence and support government policies towards mitigating climate change.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".