{"id":"W7043478898","doi":"","title":"Socialising with diversity: numerical smallness, social networks and urban superdiversity","year":2013,"lang":"en","type":"dissertation","venue":"Sussex Research Online (University of Sussex)","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Diversity (politics); Sociality; Ethnic group; Field (mathematics); Social network analysis; Focus (optics); Social network (sociolinguistics); Qualitative research; Order (exchange)","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":[0.001654571,0.0002488934,0.0002770112,0.001474569,0.002598688,0.004921266,0.0005554156,0.0004938509,0.003003329],"category_scores_gemma":[0.004467288,0.0001735695,0.0002034301,0.001684599,0.01623291,0.005097399,0.006255993,0.0007623974,0.0001157851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002057876,"about_ca_system_score_gemma":0.0008951148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006093269,"about_ca_topic_score_gemma":0.01019894,"domain_scores_codex":[0.9981337,0.001223892,0.00004911147,0.0002360216,0.0002158814,0.0001413808],"domain_scores_gemma":[0.9957889,0.002489713,0.0008064823,0.000327212,0.0002045111,0.0003831892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00008913506,0.00005091206,0.1094204,0.0003290046,0.0000722503,0.000856747,0.5332355,0.001349672,0.001759586,0.3054176,0.001229921,0.04618933],"study_design_scores_gemma":[0.00001746532,0.0001458162,0.1877794,0.0004857971,0.0000596734,0.001359141,0.554614,0.002754707,0.0006679816,0.1948826,0.0571763,0.00005701058],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9425413,0.001083859,0.00652581,0.002580459,0.00002713778,0.00002776486,0.00005225429,0.00001331875,0.04714808],"genre_scores_gemma":[0.9986795,0.000168208,0.0004996688,0.00003857812,0.000007873813,0.00001121477,0.00001124787,0.000003383089,0.0005803074],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006093269,"threshold_uncertainty_score":0.01493102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07886548815322782,"score_gpt":0.3414928879651294,"score_spread":0.2626273998119016,"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."}}