Межстрановой Анализ Отраслевой Производительности Труда В 1991-2008 Годах [International comparisons of sectoral labor productivity in 1991-2008 period]
Bibliographic record
Abstract
The article presents labor productivity estimates from 1991 to 2008 for 17 countries on industry ISIC. 3 - level. The group of countries includes USA, Canada, Brazil, Russia, Japan, China, Australia and number of major European economies. The goal is to investigate Russia`s industries comparative progress, productivity gap changes and asses possible sources for technology borrowing. In contrast to previous works analysis captures dynamics of wider country grouping on more detailed industry level. Productivity is calculated as value added per hour worked for the following industries: agriculture, hunting, forestry and fishing (A+B), mining, electricity, gas and water supply (C+E), manufacturing (D), construction (F), wholesale and retail trade, hotels and restaurants (G+H), transport (I) and others (J-P).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".