Bibliographic record
Abstract
This book fills an important gap in the knowledge about labor market conditions in Egypt in the aftermath of the Arab Spring uprisings, and it analyzes the results of the latest round of the Egypt Labor Market Panel Survey carried out in early 2012. The chapters cover topics that are essential to understanding the conditions leading to the Egyptian revolution of 25 January 2011, including the persistence of high youth unemployment, labor market segmentation and rigidity, growing informality, and the declining role of the state as an employer. It includes the first research on the impact of the revolution and the ensuing economic crisis on the labor market, including issues such as changes in earnings, increased insecurity of employment, declining female labor force participation, and the stagnation of micro and small enterprise growth. Comparisons are made to labor market conditions prior to the revolution using previous rounds of the survey fielded in 1988, 1998, and 2006. The chapters make use of this unique longitudinal data to provide a fresh analysis of the Egyptian labor market after the Arab Spring, an analysis that was simply not feasible with previously existing data. This book is essential reading for anyone interested in the economics of the Middle East and the political economy of the Arab Spring. Contributors to this volume - Mona Amer, Cairo University Ragui Assaad, University of Minnesota and the Economic Research Forum Ghada Barsoum, American University in Cairo Asmaa Elbadawy, Independent Consultant Rana Hendy, Economic Research Forum Samer Kherfi, American University of Sharjah Caroline Krafft, University of Minnesota Ali Rashed, Population Council Rania Roushdy, Population Council Mona Said, American University in Cairo Rania Salem, University of Toronto Irene Selwaness, Cairo University and the Population Council Maia Sieverding, University of California, San Francisco Jackline Wahba, University of Southampton Chaimaa Yassine, University of Paris 1
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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 | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".