{"id":"W2394628581","doi":"10.5931/djim.v12i1.6448","title":"De-myth-tifying the gender digital divide in Latin America: libraries as intermediaries in bridging the gap","year":2016,"lang":"en","type":"article","venue":"Dalhousie Journal of Interdisciplinary Management","topic":"ICT Impact and Policies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Digital divide; Mythology; Latin Americans; Intermediary; Bridging (networking); ICTS; The Internet; Construct (python library); Sociology; Information and Communications Technology; Political science; Public relations; Gender studies; Media studies; Business; Law; Computer science; World Wide Web; Marketing; History","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.009012367,0.0003927076,0.0003451954,0.002102879,0.0127381,0.02220157,0.0009557993,0.003359073,0.01241998],"category_scores_gemma":[0.007743635,0.0002595945,0.0003364025,0.002386012,0.01894691,0.01646208,0.01768346,0.003430272,0.001037019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008105149,"about_ca_system_score_gemma":0.01413167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01219662,"about_ca_topic_score_gemma":0.01690761,"domain_scores_codex":[0.9953537,0.003019479,0.00009648898,0.0002124656,0.0003615317,0.0009563147],"domain_scores_gemma":[0.9949864,0.00277844,0.000571942,0.0003265896,0.0005920358,0.0007445904],"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":[0.00006757733,0.00006572001,0.006063454,0.0001823014,0.000006716616,0.0005445115,0.1688469,0.0001108368,0.0003954526,0.7660782,0.0110752,0.04656315],"study_design_scores_gemma":[0.000015673,0.00003170378,0.003504976,0.0007230178,0.00001489921,0.0002665334,0.3646005,0.0002445996,0.0006315825,0.1390216,0.4909161,0.0000286774],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1337012,0.01329742,0.005406413,0.3553236,0.0009326254,0.00005629933,0.00005967851,0.00008028975,0.4911424],"genre_scores_gemma":[0.9411157,0.006238692,0.001409761,0.01316116,0.0003949681,0.00006520577,0.00002891935,0.00006145819,0.03752399],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02220157,"threshold_uncertainty_score":0.05880719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01772536456750298,"score_gpt":0.2600868797482552,"score_spread":0.2423615151807522,"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."}}