Bibliographic record
Abstract
Port cities across the world were deeply affected by the First World War. They had to adapt quickly to the influx of soldiers and labourers, as well as to resulting population changes that challenged and strained local structures. The pressure of these changes was especially felt in colonial port cities, as new arrivals – from abroad and from the hinterland – had the potential to undermine colonial order and control. In the period of 1914-1918 colonial authorities around the Indian Ocean saw local concerns regarding order and control overridden by global developments and imperial demands.Mombasa, located on the East African coast, provides a potent example of this situation. In the war years, Mombasa turned into a military hub, with thousands of troops passing through it to serve in the East African campaign. These external arrivals were mirrored by the movement of people from the hinterland into the city seeking to fill positions in the local war economy. In this dynamic context, racial borders, social conventions, and economic patterns were continually challenged and transgressed. This article explores these developments and reactions they triggered among Indians, Africans, and Europeans in Mombasa at the time of the global war.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.030 | 0.011 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".