{"id":"W1628984522","doi":"","title":"The Gender Digital Divide in Rural Pakistan: How Wide is it and How to Bridge it?","year":2009,"lang":"en","type":"article","venue":"Data Archiving and Networked Services (DANS)","topic":"ICT Impact and Policies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Development Research Centre","keywords":"Digital divide; Information and Communications Technology; Psychological intervention; Economic growth; Inequality; Rural area; ICTS; Political science; Business; Public relations; Psychology; Economics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.001575391,0.0002779806,0.0002977429,0.00104357,0.00699593,0.004343487,0.000607838,0.001037467,0.008280623],"category_scores_gemma":[0.002573765,0.0002129231,0.000170631,0.001500038,0.00771658,0.005687808,0.003078384,0.001618097,0.0004038492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003370033,"about_ca_system_score_gemma":0.00601221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03875959,"about_ca_topic_score_gemma":0.05788764,"domain_scores_codex":[0.9989567,0.0003745181,0.00002595843,0.0001061919,0.000135427,0.0004012115],"domain_scores_gemma":[0.9985924,0.0005016989,0.0002825695,0.00003839287,0.0001716406,0.0004132319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001670032,0.0002263894,0.127344,0.001035228,0.00002930479,0.004236697,0.574474,0.0001701878,0.001075942,0.07710271,0.02002488,0.1941136],"study_design_scores_gemma":[0.000007726681,0.0001035198,0.06350939,0.0008170831,0.00001152011,0.0007177184,0.8645123,0.00009403416,0.000170709,0.0108543,0.05916755,0.00003415185],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8098041,0.01615129,0.001246818,0.09578778,0.0007990322,0.00008763921,0.0003096384,0.00001787815,0.07579584],"genre_scores_gemma":[0.9882672,0.006083317,0.0002297676,0.002750355,0.0001112614,0.00002278099,0.00004131525,0.000003738252,0.002490271],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03875959,"threshold_uncertainty_score":0.07706797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02167612627464912,"score_gpt":0.2600585330938331,"score_spread":0.238382406819184,"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."}}