Quality and Inequality of Jobs Created in MENA Region: The Case of Labor Market in Jordan
Bibliographic record
Abstract
Using micro-level data sets, the current study constructs a Job Quality Index (JQI) for Jordanian wage and salaryworkers. Due to the unavailability of data for some years, the study covers only the period 2000–07. FactorAnalysis is utilized to compile the index based on the following four dimensions: adequate earnings;underemployment and overemployment (which together represent adequate working hours); and social security.The main findings of the study are as follows:(1) The JQI appears to have improved in 2007 compared to the mid-2000s, reaching similar levels of thoseprevailing in 2000. (2) There exists a persistent gender gap in favor of male workers, whose jobs arecharacterized by a higher JQI. This finding does not change even when taking into account other interveningvariables, particularly a worker’s age. Good jobs as a percentage of total jobs held by females appear to declinein 2007, unlike males, whose share of good jobs has grown in the same year. Therefore, no sign of convergencein job quality between males and females is detected. (3) JQI varies across education levels, however, lessobviously. Workers with basic education and lower are found to obtain considerably poorer jobs and jobsgenerally characterized with lower JQIs. (4) The JQI differs across age groups. New entrants to the labor marketand workers on the verge of retirement are more likely to have lower job quality in comparison with otherworkers belonging to age groups in the middle of their work lives. (5) The quality of jobs in agriculturalactivities is found to be on average lower than other activities. On the other hand, real estate activities tend tohave higher job quality ratings than other sectors, especially in 2007.
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How this classification was reachedexpand
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 | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".