{"id":"W4405826588","doi":"10.1017/dap.2024.85","title":"Exploring AI governance in the Middle East and North Africa (MENA) region: gaps, efforts, and initiatives","year":2024,"lang":"en","type":"article","venue":"Data & Policy","topic":"Socioeconomic Development in MENA","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto; York University","funders":"African Union; African Academy of Sciences; European Commission; African Union Commission; International Development Research Centre","keywords":"Middle East; Corporate governance; Political science; Geography; Economic growth; Development economics; Business; Economics; Archaeology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005541341,0.000210833,0.0002231205,0.001267602,0.003851289,0.004933187,0.0007845617,0.0008953097,0.004567469],"category_scores_gemma":[0.007820609,0.0001181522,0.0001661173,0.002613896,0.005472946,0.003781356,0.004225538,0.001434679,0.0001744329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006302978,"about_ca_system_score_gemma":0.01896352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03212961,"about_ca_topic_score_gemma":0.0516865,"domain_scores_codex":[0.9970446,0.001876353,0.0001110432,0.0001719557,0.000191462,0.0006046363],"domain_scores_gemma":[0.9946383,0.003663186,0.0004889983,0.000141073,0.0004881817,0.0005803208],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00008811981,0.00007985612,0.03375945,0.003722441,0.00007125469,0.001847675,0.2530257,0.001115252,0.001750693,0.4768792,0.04304061,0.1846198],"study_design_scores_gemma":[0.000009156033,0.00004473247,0.03025285,0.004659428,0.00002819708,0.0003532252,0.4686252,0.0005533643,0.0006765054,0.0505981,0.4441679,0.00003132473],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3022291,0.07734112,0.005329708,0.4382757,0.00173092,0.000151307,0.000444877,0.00005792294,0.1744393],"genre_scores_gemma":[0.9556616,0.02933346,0.00267752,0.006503333,0.0002230946,0.0001202646,0.0001102766,0.00001839381,0.005352085],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03212961,"threshold_uncertainty_score":0.06388521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3537345896055294,"score_gpt":0.339661056364343,"score_spread":0.01407353324118649,"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."}}