Bibliographic record
Abstract
The economic performance of Vietnam in the 1990s would be classified as a ‘miracle’ if such achievements were not so common in Asia in the latter half of the twentieth century. GDP growth rates between 8.1 per cent and 9.5 per cent during 1992–97 were led by industry and services, though the agriculture sector growth also increased by an impressive 4.8 per cent per annum. Transition, typically identified as ‘starting’ in 1986, was a relatively painless affair of structural adjustment and stabilization for the first decade. The state sector was never large in Vietnam, where 80 per cent of the population lives in rural areas, mostly growing rice. By 1986 the planned part of the economy was thoroughly undermined, and inflation had eroded any monetary overhang. The collapse of the Council of Mutual Economic Assistance (CMEA) trading relationship forced restructuring in the state-owned enterprise sector, which shed almost one-quarter of its workforce (see below). However, institutional reforms created a boom in the urban household economy that absorbed the unemployed. The shift in employment was relatively easy, without the burden of a large military-industrial complex, and Vietnam’s exports to the CMEA found new Western buyers with relative ease. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 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".