{"id":"W2802755385","doi":"10.5539/ijel.v8n4p192","title":"A Semiotic Analysis of Gender Discursive Patterns in Pakistani Television Commercials","year":2018,"lang":"en","type":"article","venue":"International Journal of English Linguistics","topic":"Media, Gender, and Advertising","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Semiotics; Nonprobability sampling; Meaning (existential); Ideology; Sociology; Representation (politics); Narrative; Social semiotics; Linguistics; Psychology; Advertising; Social psychology; Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001241059,0.0002325424,0.0001718147,0.004078016,0.002644189,0.003406094,0.0003211942,0.0003872618,0.002825908],"category_scores_gemma":[0.003593317,0.0001734214,0.0001802477,0.004340721,0.004240586,0.001716556,0.001385334,0.0004304319,0.0002208945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001884538,"about_ca_system_score_gemma":0.0009583736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006065246,"about_ca_topic_score_gemma":0.007951091,"domain_scores_codex":[0.9989692,0.0005155967,0.00005556877,0.0001045232,0.0002343284,0.0001207484],"domain_scores_gemma":[0.9965475,0.002120933,0.0004565789,0.000173508,0.0005628053,0.0001386324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001087288,0.00004078664,0.02708094,0.0001971263,0.000009858589,0.001892828,0.9016962,0.00007247459,0.004660876,0.02204769,0.001139914,0.04105256],"study_design_scores_gemma":[0.00000456166,0.00005343769,0.07618076,0.0001390701,0.00001159261,0.001106699,0.8986522,0.0004049188,0.001331357,0.003691995,0.01840231,0.00002112066],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.959958,0.0005027917,0.002894353,0.0005019435,0.00002998547,0.0000782471,0.0001962226,0.0000151443,0.03582331],"genre_scores_gemma":[0.9973872,0.0002103419,0.0008664643,0.00002086816,0.00001061328,0.00003122022,0.00006557118,0.000005570776,0.001402181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006065246,"threshold_uncertainty_score":0.01367331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04065369893309788,"score_gpt":0.3800448034983873,"score_spread":0.3393911045652894,"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."}}