{"id":"W1508830161","doi":"","title":"Egypt Labor Market Panel Survey 2006: Report on Methodology and Data Collection","year":2007,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Underemployment; Earnings; Sample (material); Data collection; Unemployment; Panel data; Work (physics); Scale (ratio); Demographic economics; Survey data collection; Survey sampling; Business; Geography; Economics; Economic growth; Engineering; Finance; Sociology; Demography; Statistics; Population","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006119474,0.001090559,0.0009473581,0.00252528,0.0004692578,0.001056858,0.001466334,0.0006240139,0.02489488],"category_scores_gemma":[0.007941607,0.0005389762,0.0005613375,0.006172484,0.0002131636,0.0008108215,0.001017984,0.001152859,0.01607896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00295826,"about_ca_system_score_gemma":0.004246677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04233726,"about_ca_topic_score_gemma":0.04598979,"domain_scores_codex":[0.9982051,0.000488221,0.0002756195,0.0001808962,0.0006058204,0.0002444041],"domain_scores_gemma":[0.9932424,0.0006649259,0.0007651813,0.0006421419,0.004427765,0.0002576562],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002951083,0.0001574129,0.02370766,0.0007121848,0.0001081065,0.00008278708,0.000361834,0.0008034671,0.0002552029,0.001596041,0.9248287,0.04709145],"study_design_scores_gemma":[0.0002508284,0.0001162631,0.2607142,0.0004334124,0.00007949665,0.0001149406,0.0006096673,0.0006704023,0.0008315988,0.0007982782,0.735306,0.00007480101],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.008854437,0.0005522289,0.002502537,0.0009209097,0.0001574717,0.003217842,0.9735995,0.0003228421,0.009872295],"genre_scores_gemma":[0.02356193,0.001750098,0.01208176,0.0009556683,0.0001497127,0.0101476,0.9289638,0.000213879,0.02217561],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.04233726,"threshold_uncertainty_score":0.08418167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2499667148132282,"score_gpt":0.4610547633293366,"score_spread":0.2110880485161084,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}