{"id":"W2028958621","doi":"10.3390/educsci3010030","title":"Who Needs to Fit in? Who Gets to Stand out? Communication Technologies Including Brain-Machine Interfaces Revealed from the Perspectives of Special Education School Teachers Through an Ableism Lens","year":2013,"lang":"en","type":"article","venue":"Education Sciences","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Ableism; Perception; Judgement; Special education; Psychology; Normality; Pedagogy; Applied psychology; Mathematics education; Social psychology; Sociology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.004507592,0.0005114107,0.0005246226,0.001335308,0.008346416,0.01030928,0.0009260685,0.002196289,0.00187556],"category_scores_gemma":[0.00618856,0.0004424529,0.0003851472,0.0008896836,0.02138209,0.005421742,0.006019843,0.006220154,0.0003053047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005047734,"about_ca_system_score_gemma":0.004553182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02655751,"about_ca_topic_score_gemma":0.03851213,"domain_scores_codex":[0.9952159,0.002657377,0.0001202877,0.0003032816,0.0006824409,0.001020753],"domain_scores_gemma":[0.9943032,0.003024222,0.0006696154,0.0001647015,0.0005619374,0.001276332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001022509,0.00001272901,0.003748644,0.00004347326,0.000002248974,0.0005859504,0.9879852,0.00001407404,0.0004906882,0.003934078,0.0005530407,0.002619609],"study_design_scores_gemma":[8.56024e-7,0.000006910633,0.001209577,0.00003881143,0.000001823075,0.0001785018,0.9918196,0.00002057897,0.00007724282,0.000553617,0.006087503,0.000005002145],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9353701,0.001647455,0.00300236,0.02610266,0.0002049438,0.00003638972,0.00004021415,0.00002194778,0.03357398],"genre_scores_gemma":[0.9951637,0.0006635293,0.0002759075,0.001193835,0.00002563656,0.00001369468,0.00001065146,0.00001075059,0.002642328],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02655751,"threshold_uncertainty_score":0.05280584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0779464028464225,"score_gpt":0.3719006545145003,"score_spread":0.2939542516680778,"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."}}