{"id":"W4308614086","doi":"10.15581/004.39.39599","title":"Handbook on Measuring Equity in Education (2018). Montréal: UNESCO Institute for Statistics, 142 pp.","year":2020,"lang":"es","type":"article","venue":"Estudios sobre Educación","topic":"Evaluation and Performance Assessment","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Equity (law); Statistics; Library science; Mathematics education; Sociology; Regional science; Political science; Psychology; Mathematics; Computer science; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002563821,0.0004716612,0.0007074516,0.0002879282,0.0004935132,0.0005656968,0.000805853,0.0001777386,0.0003424127],"category_scores_gemma":[0.003378051,0.0004254996,0.0001668055,0.0008993564,0.0001794218,0.0007859993,0.0002920025,0.0004477401,0.001275195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005689383,"about_ca_system_score_gemma":0.004122764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003941671,"about_ca_topic_score_gemma":0.0009413469,"domain_scores_codex":[0.994806,0.0002722006,0.001277576,0.001056501,0.001937034,0.0006506906],"domain_scores_gemma":[0.9968314,0.000779408,0.0005325693,0.0006587638,0.0007538398,0.0004439758],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004590243,0.001426747,0.02737678,0.0003808053,0.0001000439,0.000008209002,0.005839554,0.003859273,0.0002273284,0.02832828,0.3973568,0.5346372],"study_design_scores_gemma":[0.003182784,0.001300648,0.0719458,0.001099088,0.0001521525,0.000005748937,0.005974626,0.01164428,0.00108004,0.005597311,0.8969488,0.001068683],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4556208,0.05626237,0.09091169,0.2704309,0.07573775,0.01772722,0.002778824,0.0006148828,0.02991562],"genre_scores_gemma":[0.9752548,0.004902455,0.009901633,0.005207225,0.002398794,0.0005261972,0.0001570652,0.00006946007,0.0015824],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5335684,"threshold_uncertainty_score":0.9998197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2091034941127479,"score_gpt":0.4603794936033102,"score_spread":0.2512759994905623,"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."}}