Bibliographic record
Abstract
Abstract Maputo (Lourenço Marques until 1976) is the capital of Mozambique and one of the busiest port cities on the east coast of Africa. The Bay of Lourenço Marques had already been a source of ivory for the Indian Ocean world and Europe for centuries when, in the late 18th century, Portugal established a permanent garrison there, among the Mpfumo and other Xi-ronga-speaking clans. From 1898 until independence in 1975, the fort-turned-city was the administrative headquarters of Portugal’s territory of Mozambique, a home to many Portuguese settlers, and a stark example of racialized exploitation and urban segregation under colonial rule. It was also the principal transit hub for hundreds of thousands of southern Mozambican men recruited to labor in neighboring South Africa. Following independence, the city became a laboratory of revolutionary socialist experimentation as well as an overcrowded safe haven for refugees of Mozambique’s long and terrible civil war. Despite closer historical ties to South Africa than to most of Mozambique, Maputo is the country’s economic center and its gateway for foreign investment. According to 2017 census figures, the metropolitan population exceeded 2.5 million, making it one of the larger urban areas in southern Africa.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.574 | 0.255 |
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".