Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Indonesia has responded with a bold and comprehensive policy package to cushion the impact of the COVID-19 pandemic. The economy rebounded in the third quarter of 2020, and the economic recovery is projected to strengthen in 2021 and 2022. Strong policy support and an improving global economy will be the main drivers initially, and greater mobility and confidence will follow with the planned vaccination program in 2021. The uncertainty surrounding the growth outlook is larger than usual. Early completion of a widespread vaccination program is an upside risk, while a protracted pandemic remains a downside risk. The macro-financial fallout of the pandemic and economic downturn could be larger than expected, and credit conditions could be slow to improve. Ongoing reforms aimed at promoting investment are expected to help mitigate the scarring effects from the pandemic and put the economy on a sustained growth path that builds on Indonesia’s favorable demographics.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it