QUARTERLY ANALYSIS: The Progress of Monetary, Banking and Payment System, First Quarter – 2013
Bibliographic record
Abstract
Indonesia’s economy in the first quarter 2013 growth slowed compared to the previous quarter. Economic growth stood at 6.02% (yoy), lower than the previous quarter grew by 6.11% (yoy). A source of slowing growth came from domestic demand amid declining export performance. Slowing growth in household consumption was due to the decrease in purchasing power as a result of an increase in inflationary pressures, especially food. In addition, government consumption growth is relatively low, due to the limited uptake of spending, especially spending on goods. A decline also occurred in investment performance, particularly non-construction that is influenced by limited domestic and international demand outlook. Decline in investment performance is in line with the decline in business optimism. In non-construction investment, there is reduced performance in machinery investment, in line with the slowdown in the imports of capital goods. In contrast, exports showed improvement, supported by strengthening expectations of global economic recovery and rising volume of world trade. Response to slowing domestic demandsaw a contraction in imports. Sources of downward import pressure are from the imports of raw materials and capital goods, mainly raw materials for the industrial and passenger vehicle industry which has seen a slowdown and moderation in response to motor vehicle sales.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".