Bibliographic record
Abstract
With a GDP growth rate of 16% 2009, jumping from 7 billion dollars in 1984 to $95 billion 2009 (Qatar statistic authority and world bank 2010), ranking second in per capita income of $121000 for 2009 climbing from 20000$ 1984 (world bank 2010), economic freedom world rank 39th of 170 countries, the second in the region 17 countries (2010 IEF), holding some of the world biggest industrial manufacturing in diversified sectors like: oil refinery, liquid natural gas, aluminum, urea, weather cooling systems… Attracting Foreign Investment facilities: independent judiciary, transparent governance ranking the 28th out from 179 countries and stating a legal authorized business take only 6 day compared with world average of 35days (2010 IEF), The GCC member state of Qatar realize an important increase of its economy integration into the global markets, what let the state get hold more confidence of many international partners, and help Qatar to win the bid against USA of 2022 cup organization!But for which level the indicators of Qatar economy can match more the emerging markets requirements set by world economic known institution?This study tends to apply, key selected macroeconomic descriptive framework based on indicators and ratios taken from the international comparison program ICP, into the Qatar economic data to test its responding level. We base also on the literature review that defines and measures the emerging markets economics.This research’ findings give a high percentage for the conforming of the Qatar economy indicators to the measurement and standards of emerging markets defined by WTO, WB, IMF and compared by many other world economic high institutions, and open the door to expand the research for new economic classification for world countries, the last one on the issue was done 2005. It may also help clarify some steps in taking decision in developing future strategies for the like-minded countries of the region.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".