{"id":"W3203618922","doi":"10.29173/iasl8272","title":"Turning Advocacy into Action: Inclusive Makerspaces","year":2021,"lang":"en","type":"article","venue":"IASL Annual Conference Proceedings","topic":"Library Science and Administration","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Variety (cybernetics); Cognitive disabilities; Special needs; Special education; Special populations; Action (physics); Population; Inclusion (mineral); Pedagogy; Psychology; Cognition; Public relations; Sociology; Political science; Medical education; Medicine; Computer science; Social psychology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003721827,0.00013186,0.0001458045,0.00006587107,0.001046346,0.0007729027,0.0003187177,0.0001219891,0.0006898444],"category_scores_gemma":[0.0006356365,0.0001304602,0.0000543353,0.0006752944,0.0003336646,0.003642908,0.0001363328,0.0002043568,0.0001035013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006905687,"about_ca_system_score_gemma":0.001716591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004120491,"about_ca_topic_score_gemma":0.0004040798,"domain_scores_codex":[0.9984915,0.00003429882,0.0001794431,0.0003859735,0.0005446624,0.0003640743],"domain_scores_gemma":[0.99862,0.0000547294,0.0001273837,0.00006673032,0.0009116084,0.0002195538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001952937,0.00005479076,0.01351481,0.00003267438,0.00001286531,0.00002223055,0.9210461,8.716054e-7,0.003172503,0.03891873,0.007768186,0.01543669],"study_design_scores_gemma":[0.0001377278,0.00007384239,0.003041361,0.00005845646,0.000009427018,0.000008744391,0.8170797,0.00004725477,0.007740942,0.01574905,0.1558137,0.0002398322],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9102557,0.00008672786,0.0001248361,0.02874524,0.0003852914,0.0001276594,0.000003191929,0.0001637313,0.06010759],"genre_scores_gemma":[0.9888725,0.0001226584,0.0009468379,0.0008600317,0.0005405796,0.00001268648,0.000007762555,0.000006879911,0.008630022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1480455,"threshold_uncertainty_score":0.8047755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03657864622223422,"score_gpt":0.3409932141622791,"score_spread":0.3044145679400448,"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."}}