Measuring the Spatial Correlation of Unemployment in Iraq-2007
Why this work is in the frame
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Bibliographic record
Abstract
Although many studies examined the existence of spatial pattern of unemployment in some developing and many developed countries in improving the prosperity or social status and reducing the inequalities in unemployment between areas of such country, there is still much work to be done. Some of these studies were found spatial pattern for unemployment using different statistical techniques and geographical mapping. Question is raised whether the spatial pattern of unemployment is existed in Iraq? The objective is to investigate the spatial structure of unemployment rate (UR) across different governorates to provide implications for policy makers, investigating the hot spots of UR, and showing visual picture for UR. The study utilized a cross-sectional census data for 18 governorates collected in 2007. Mapping was used as a first step to conduct visual inspection for UR using quartiles. Two statistics of spatial autocorrelation, based on sharing boundary neighbours, known as global and local Moran's I, were carried out for examining the global clustering and local clusters respectively. Based on visual inspection of mapping, the global clustering was found in UR and it was confirmed by the significant statistic found by global Moran’s I . Out of 18, seven governorates: 3, 4, 5, 12, 15, 16, and 17 were found as local clusters in UR based on local Moran's I. In conclusion, the UR varied across different governorates with black spots in northern and southern parts of the country.
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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 | 0.001 | 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) | 0.000 | 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