{"id":"W2793669535","doi":"10.5539/jel.v7n3p11","title":"Contradictions as Drivers for Improving Inclusion in Teaching Pupils with Special Educational Needs","year":2018,"lang":"en","type":"article","venue":"Journal of Education and Learning","topic":"Collaborative Teaching and Inclusion","field":"Social Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mainstream; Special educational needs; Mainstreaming; Inclusion (mineral); Thematic analysis; Pedagogy; Special education; Mathematics education; Psychology; Subject (documents); Special needs; Sociology; Qualitative research; Political science; Social psychology; Social science; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.02622396,0.000452085,0.0008102391,0.003397473,0.007492451,0.009670668,0.001563996,0.00176097,0.001617086],"category_scores_gemma":[0.04566899,0.0008676097,0.0006163371,0.00212174,0.01761803,0.007008496,0.01463101,0.002818989,0.0001270096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007578439,"about_ca_system_score_gemma":0.01041372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003694243,"about_ca_topic_score_gemma":0.004186655,"domain_scores_codex":[0.9729558,0.015382,0.002099539,0.00129522,0.005871012,0.00239633],"domain_scores_gemma":[0.9551128,0.0277361,0.008576088,0.002370588,0.004085393,0.002119106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0000868926,0.00009818952,0.05714412,0.0006388997,0.00007594824,0.001688432,0.8272663,0.0004945552,0.00240405,0.07703464,0.0006233184,0.03244454],"study_design_scores_gemma":[0.00003359454,0.0001251903,0.04610825,0.0007421804,0.0001198308,0.001371774,0.849501,0.001685845,0.002169751,0.07425786,0.02376813,0.0001165497],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9600819,0.001106517,0.01068409,0.007029754,0.00007199366,0.0001067304,0.0000315076,0.00004152654,0.02084606],"genre_scores_gemma":[0.9975737,0.0001543272,0.001815456,0.0000891553,0.00000652135,0.00002742898,0.000008936244,0.000007164249,0.0003173736],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02622396,"threshold_uncertainty_score":0.1386872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01048888839853349,"score_gpt":0.3357761232751482,"score_spread":0.3252872348766147,"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."}}