{"id":"W298741439","doi":"10.18806/tesl.v18i1.898","title":"Gender Positioning in Education: A Critical Image Analysis of ESL Texts","year":2000,"lang":"en","type":"article","venue":"TESL Canada Journal","topic":"Gender Studies in Language","field":"Social Sciences","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Interrogation; Politics; Sociology; Identification (biology); Critical discourse analysis; Point (geometry); Critical mass (sociodynamics); Semantic analysis (machine learning); Pedagogy; Linguistics; Social science; Political science; Law; Computer science; Artificial intelligence","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000477176,0.00006468681,0.0001745981,0.0001718268,0.0003891201,0.00005139482,0.0001907631,0.00003228947,0.05714313],"category_scores_gemma":[0.0003219123,0.0000664618,0.00006530981,0.0008708749,0.0001512725,0.0001261565,0.00001337258,0.0001872271,0.000002396648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005201507,"about_ca_system_score_gemma":0.002756121,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.325623,"about_ca_topic_score_gemma":0.6085367,"domain_scores_codex":[0.9986619,0.0001642895,0.000261199,0.000106859,0.0005263042,0.0002794797],"domain_scores_gemma":[0.9993896,0.0001415669,0.00005434644,0.0001011383,0.000167256,0.0001460202],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001144085,0.001313867,0.08134088,0.000113589,0.003354781,0.001395805,0.2840345,0.002253924,0.0005532854,0.05674642,0.3713869,0.1973916],"study_design_scores_gemma":[0.0008409116,0.00007633834,0.7169764,0.0001319455,0.00156067,0.0001598195,0.1583343,0.0004372636,0.00009595445,0.008576025,0.1118833,0.0009271028],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5410939,0.04088833,0.0002352266,0.01126039,0.001194667,0.0001893474,0.00003983395,0.0000270084,0.4050712],"genre_scores_gemma":[0.9931064,0.00006202654,0.001374767,0.004920538,0.0002015515,0.000002565041,0.000001715698,0.000004754011,0.0003257248],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6356356,"threshold_uncertainty_score":0.9437188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0132885555456465,"score_gpt":0.3389098900772259,"score_spread":0.3256213345315794,"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."}}