Russia Economic Report, November 2017, No. 38: Russia’s Recovery—How Strong Are Its Shoots?
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
Global growth gained momentum in 2017. After slowing to 2.4 percent in 2016 as investment and trade weakened, global growth accelerated to a projected 2.7 percent for 2017.Moreover, the recovery has been broad-based.Global trade also continued to strengthen and external financing conditions remain benign.Amid these positive tailwinds, along with firming oil prices and growing macro-stability, the Russian economy returned to modest growth in 2017. The growth momentum of the second half of 2016 spilled over to 2017 and was especially strong in the second quarter this was supported by a rebound in domestic demand in the first half of 2017-which also contributed to a growth slowdown starting in the third quarter.On the production side, mineral resource extraction, transportation, and state management and provisioning for national security drove growth in the first quarter of 2017.Monetary policy remained prudent and consistent with the inflation-targeting framework. However, improvement in headline indicators masks underlying disparities and remaining vulnerabilities
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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