Climate change and coastal cities: the case of Mombasa, Kenya
Bibliographic record
Abstract
This paper discusses the risks that the city of Mombasa faces from the direct and indirect impacts of climate change. Mombasa is Kenya's second largest city and has more than 700,000 inhabitants. It is the largest seaport in East Africa, serving not only Kenya but also many landlocked countries and the north of Tanzania. The city has a history of disasters related to climate extremes including floods, which cause serious damage nearly every year and, often, loss of life. The floods in October 2006 were particularly serious, affecting some 60,000 people in the city and the wider province. In addition, around 17 per cent of Mombasa's area could be submerged by a sea-level rise of 0.3 metres, with a larger area rendered uninhabitable or unusable for agriculture because of water logging and salt stress. Tourism is an important part of the city's economy. Thus, sandy beaches, historic and cultural monuments and several hotels, industries and port facilities would be negatively affected. This paper also discusses the measures needed to reduce the vulnerability of Mombasa's population and economic base to climate change.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".