Armenia Country Economic Update, Fall/Winter 2017-18 : A Window of Opportunity to Tackle Challenging Reforms
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
The World Bank expects the Armenian \n economy to grow about 4 percent in 2017 with a modest but \n sustained recovery envisaged over the medium term. After \n stagnating in 2016, the economy showed renewed and \n greater-than-expected strength in the first half of 2017, \n which has continued into the third quarter but at a \n moderated pace. Higher gross domestic product (GDP), along \n with improvements in tax administration, have contributed to \n an improvement in tax collection, which has permitted some \n loosening of the earlier compression of capital \n expenditures. Having exceeded the fiscal rule’s lower \n debt-to-GDP threshold (50 percent), the deficit has been \n constrained to below 3 percent of GDP this year. This issue \n of the Armenia country economic update includes a special \n section on population, migration, and growth. It highlights \n the extent to which net out migration has driven Armenia’s \n population dynamics, how it may affect longer term growth, \n and the types of policies that can stem the outflow of \n Armenia’s best and brightest young people.
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 | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.011 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.014 |
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