Bibliographic record
Abstract
SUMMARYThe political authority of President Joko Widodo (Jokowi) was bolstered in the third quarter of 2015 by a cabinet reshuffle, his coalition's gaining a parliamentary majority, and several foreign-policy developments. Indonesia's request to rejoin OPEC, for example, after having left in 2008, seemed more about international relations than oil prices, while official visits to the Middle East and the United States allowed Jokowi to project his presidency on the international stage. He still faces resistance from within his own party, however.Jokowi's politically bold reshuffle of economic ministers in August soon yielded a range of policy announcements. In September and October, his government introduced its first substantial set of reforms—a number of economic policy packages intended, among other things, to attract investment and stimulate domestic demand. If even half of these policies are put in place, the impact on Indonesia's economy should be tangible.Few countries have escaped the effects of falling global commodity prices and China's growth slowdown. At 4.7%, year on year, in the third quarter Indonesia's rate of economic growth again fell short of the government's target. Slowing growth and a negative outlook have lowered market expectations and weakened the rupiah, which is also burdened by the large outstanding external debt held by corporate borrowers. Indonesia's real effective exchange rate has recently begun to depreciate, however, which may stimulate exports. Growth prospects will also improve if the substantial increase in capital and infrastructure spending allocated in the state budget is realised.Against this backdrop, we focus on what has happened to poverty and inequality in Indonesia since Jokowi took office. The distributional impacts of the current macroeconomic climate are likely to be hardest felt by the poor. Indonesia is well known for its record on poverty reduction, but between September 2014 and March 2015 the share of the population in poverty increased, even though economic growth was close to 5.0%. Slowing growth, rising food prices, the falling real wages of farmers, and the delayed disbursement of fuel-price compensation all had an effect. Such impacts may be mitigated in the medium term by Jokowi's budget reallocations to infrastructure, if realised, and his expansion of social spending.
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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 | 0.002 |
| 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 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".