{"id":"W2810511658","doi":"10.1111/nana.12446","title":"Mapping institutional mechanisms of ethno‐national representation: towards a better measurement approach","year":2018,"lang":"en","type":"article","venue":"Nations and Nationalism","topic":"Electoral Systems and Political Participation","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada; University of Toronto","keywords":"Representation (politics); Argument (complex analysis); Politics; Computer science; State (computer science); Set (abstract data type); Management science; Sociology; Political science; Economics; Law; Algorithm","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0281824,0.0004688668,0.0006979679,0.01028037,0.001835127,0.007433715,0.00194729,0.0008575623,0.002862515],"category_scores_gemma":[0.06327389,0.0004425529,0.0006580593,0.01048287,0.007375266,0.006699594,0.007491259,0.001228204,0.0002345496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003763956,"about_ca_system_score_gemma":0.003659148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004044878,"about_ca_topic_score_gemma":0.004289662,"domain_scores_codex":[0.9670935,0.02545433,0.00212656,0.001832755,0.002845438,0.0006474205],"domain_scores_gemma":[0.9339224,0.03745124,0.01101045,0.01093299,0.005818893,0.0008640108],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009862972,0.0002667664,0.4021818,0.0008994038,0.0003287541,0.0001038445,0.03832472,0.007474735,0.001847364,0.3498431,0.001562684,0.1970682],"study_design_scores_gemma":[0.00005294273,0.0005050104,0.5076414,0.002038127,0.000231746,0.0003463618,0.09734218,0.03714431,0.006386759,0.3042315,0.04386761,0.0002120545],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5313004,0.001189531,0.4050769,0.00283739,0.0000921232,0.0009932431,0.001288335,0.000268426,0.05695364],"genre_scores_gemma":[0.9254461,0.000229966,0.07275422,0.00008509767,0.00002538482,0.0007107783,0.0002616597,0.00002635557,0.0004603644],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0281824,"threshold_uncertainty_score":0.1490446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1841790478397382,"score_gpt":0.3913885427782631,"score_spread":0.2072094949385249,"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."}}