Maldives Development Update, October 2023: Batten Down the Hatches
Bibliographic record
Abstract
The economy has maintained its strong growth momentum, with the expansion in tourism, and poverty is expected to fall further in 2023. The number of tourist arrivals grew by 14 percent (y-o-y) to 1.25 million by early September 2023, reaching a historic high compared to similar periods in other years (Figure ES.1). Despite the Russian invasion of Ukraine, arrivals from Russia remained strong. An earlier-than-expected reopening of the Chinese market, on January 18, has compensated for lower arrivals from India and Gulf countries, while arrivals from Europe continued to increase. As a result, the Maldivian economy grew by 5.5 percent (y-o-y) in the first quarter of 2023. Poverty levels also fell with the strong economic rebound, to an estimated level of 1.5 percent of the population. High inequality in the country, especially in the outer atolls, remains a real concern.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.095 | 0.037 |
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".