Analysis of Economic Growth Rates in East Java During the Covid-19 Period
Bibliographic record
Abstract
Introduction/Main Objectives: This study aims to determine economic growth during the Covid-19 period in East Java for 2019-2021. Research Methods: This study used a qualitative method using a library research approach. Finding/Results: Based on the study's results, economic growth during the Covid-19 period in East Java for the 2019-2021 period experienced a drastic decline. In quarter IV-2020 against quarter IV-2019 (y-on-y), East Java's economy contracted by 2.64 percent. In the first quarter of 2020, growth began to slow down to 2.97 percent. Furthermore, in the second quarter of 2020, it contracted to 5.98 percent compared to the second quarter of 2019. And in the second quarter of 2021, economic conditions began to improve even though they were still contracting, namely by 7.05 percent. Conclusion: The government must be able to provide policies that can increase economic growth because economic growth is a reference for the level of social welfare in real terms.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".