{"id":"W2138038851","doi":"10.3968/j.ccc.1923670020130906.2657","title":"Construction of Differences Through Movies: A Case Study of Portrayal of Kashmiri Muslims in Indian Movies","year":2013,"lang":"en","type":"article","venue":"Cross-cultural communication","topic":"South Asian Studies and Conflicts","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Kashmiri; Audience measurement; Context (archaeology); Simple random sample; Representation (politics); Terrorism; Content analysis; Media studies; Population; Advertising; Geography; History; Sociology; Social science; Political science; Demography; Law; Politics","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":[0.0002668267,0.000104685,0.0003115992,0.0000512091,0.0003600904,0.00005814484,0.0003585434,0.00008453674,0.00005205146],"category_scores_gemma":[0.0002384645,0.0000837314,0.00005858639,0.0003807618,0.001665105,0.0005547872,0.0001167514,0.0001204224,0.000001933887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000349753,"about_ca_system_score_gemma":0.00005192144,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07655577,"about_ca_topic_score_gemma":0.02220982,"domain_scores_codex":[0.9986714,0.0002447021,0.0005496703,0.0001311793,0.0002422039,0.0001608272],"domain_scores_gemma":[0.9983683,0.0001802567,0.0004854092,0.000374726,0.0005590621,0.0000322906],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001273757,0.0001961683,0.354796,0.00004212321,0.00003788265,0.000002868185,0.6351784,0.000004023654,0.0001273718,0.002286001,0.000008484534,0.00730799],"study_design_scores_gemma":[0.0004536408,0.0001136883,0.1722987,0.00005361095,0.00001305531,0.000006613836,0.8261708,0.000006046273,0.0001144691,0.0006076297,0.00008093549,0.00008082645],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939322,0.0003743666,7.256152e-7,0.0001893177,0.00005380225,0.0005725384,0.000008267419,0.00001707815,0.004851633],"genre_scores_gemma":[0.9992596,0.0003295314,0.0002734951,0.000009910274,0.0000148411,0.00005745322,0.000005312492,0.000003983874,0.000045876],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1909924,"threshold_uncertainty_score":0.9956323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05100075635169777,"score_gpt":0.3699372127836489,"score_spread":0.3189364564319511,"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."}}