Employment Recovery in Europe and Central Asia
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
Despite high unemployment in most \n Eastern Europe and Central Asia (ECA) countries, people have \n not withdrawn from the labor market but continue to actively \n look for jobs. Unemployment increased significantly in ECA \n countries during the crisis, particularly among youth. \n However, young people are also the ones benefiting most from \n the recovery. Labor market recovery remained sluggish up to \n the third quarter of 2010. Many countries have seen only a \n slight recovery in unemployment rates, although output is \n recovering everywhere. Up to the third quarter of 2010, the \n Gross Domestic Product (GDP) upturn in most ECA countries \n appeared to be driven by increases in productivity and hours \n worked; however, these are still below pre-crisis levels. \n This suggests that there is room in most countries for \n further increases in productivity and hours worked, which \n could delay the recovery in employment.
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 | 0.000 | 0.000 |
| 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) | 0.001 | 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