{"id":"W2140340783","doi":"","title":"Catching up with the Swedes: Probing the Canada-Sweden Literacy Gap","year":2000,"lang":"en","type":"preprint","venue":"Munich Personal RePEc Archive (Ludwig Maximilian University of Munich)","topic":"Education Systems and Policy","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Literacy; Secondary education; Front (military); Economic growth; Information literacy; Adult literacy; Public relations; Political science; Pedagogy; Sociology; Geography; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005512277,0.000333341,0.0007755377,0.007801274,0.01556621,0.009901593,0.00173365,0.001395586,0.005943201],"category_scores_gemma":[0.01304587,0.0003106081,0.000373079,0.01490501,0.005903847,0.003998221,0.008928603,0.002569622,0.0004576146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06805996,"about_ca_system_score_gemma":0.1036267,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9851628,"about_ca_topic_score_gemma":0.9928187,"domain_scores_codex":[0.9946229,0.0006475255,0.0002087434,0.0003768649,0.001491016,0.002652837],"domain_scores_gemma":[0.9897768,0.002697422,0.000844876,0.0002075958,0.004221706,0.002251521],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0003830668,0.0002409254,0.2644408,0.0006112233,0.00009044851,0.001728209,0.5166515,0.0002055134,0.0003383349,0.06995525,0.04484411,0.1005106],"study_design_scores_gemma":[0.00001814261,0.00004146612,0.1458528,0.0007505938,0.00005560773,0.0001376738,0.7892638,0.0001560383,0.0001909016,0.001941272,0.06154915,0.00004253691],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9110398,0.005902804,0.0002333732,0.02774836,0.0002030422,0.00006336989,0.001661883,0.00001442364,0.05313292],"genre_scores_gemma":[0.9836699,0.003173122,0.0002536923,0.003136947,0.00003462291,0.00006460569,0.0007765369,0.00002516932,0.008865396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06805996,"threshold_uncertainty_score":0.4938118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03497068244371759,"score_gpt":0.2792837185955244,"score_spread":0.2443130361518068,"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."}}