{"id":"W2010664765","doi":"10.1145/820127.820188","title":"Gender and information technology","year":2002,"lang":"en","type":"article","venue":"ACM SIGCSE Bulletin","topic":"Gender and Technology in Education","field":"Social Sciences","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Discipline; Variety (cybernetics); Government (linguistics); Information technology; Public relations; Matching (statistics); Sociology; Convergence (economics); Engineering ethics; Political science; Social science; Engineering; Law; Economic growth; Computer science; Economics; Medicine","routes":{"ca_aff":true,"ca_fund":false,"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":["sts"],"consensus_categories":[],"category_scores_codex":[0.003743144,0.000413207,0.0004339191,0.002257264,0.003656148,0.007103339,0.0005500645,0.001286325,0.0126731],"category_scores_gemma":[0.008959658,0.0001225737,0.0002806979,0.00275928,0.01055517,0.0051092,0.004123751,0.001274975,0.0009888686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002655685,"about_ca_system_score_gemma":0.001636282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002475658,"about_ca_topic_score_gemma":0.00175549,"domain_scores_codex":[0.9954544,0.002756605,0.0001262454,0.0003596751,0.0006244558,0.0006785629],"domain_scores_gemma":[0.9927907,0.004656771,0.000932358,0.0002416346,0.0004475178,0.0009309897],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00005091366,0.0000391707,0.007721603,0.0001510432,0.00001378229,0.0002859026,0.06768871,0.0001022018,0.0001946242,0.8751597,0.006081881,0.0425106],"study_design_scores_gemma":[0.00002128043,0.000145015,0.01533123,0.0009890376,0.0000262545,0.001391151,0.1037776,0.0001666695,0.0003771583,0.3352379,0.5424912,0.0000453857],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1503508,0.04640504,0.00705177,0.05681888,0.001695683,0.00005638182,0.0002550638,0.00005228578,0.7373142],"genre_scores_gemma":[0.9578314,0.01233276,0.0008659298,0.004256949,0.0004836694,0.00005243829,0.0000588931,0.00002727279,0.02409064],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9963439,"threshold_uncertainty_score":0.04239577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0257160157195255,"score_gpt":0.2687064808119452,"score_spread":0.2429904650924197,"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."}}