{"id":"W2874077104","doi":"10.19173/irrodl.v19i3.3538","title":"Differential OER Impacts of Formal and Informal ICTs: Employability of Female Migrant Workers","year":2018,"lang":"en","type":"article","venue":"The International Review of Research in Open and Distributed Learning","topic":"Open Education and E-Learning","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Employability; Formal learning; Informal learning; Context (archaeology); Open educational resources; Livelihood; Sociology; Public relations; Economic growth; Business; Political science; Knowledge management; Pedagogy; Economics; Geography; Computer 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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.001188183,0.0001479558,0.000167631,0.0004107236,0.0004753366,0.001117254,0.0002402,0.0003194462,0.002804624],"category_scores_gemma":[0.003287549,0.00007493114,0.000216909,0.0004453598,0.0005602332,0.0007722468,0.001480387,0.0003014067,0.0002350399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002932702,"about_ca_system_score_gemma":0.0005571247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002738887,"about_ca_topic_score_gemma":0.006062482,"domain_scores_codex":[0.9991517,0.0004135915,0.00005254554,0.00007837061,0.0001119933,0.0001918117],"domain_scores_gemma":[0.9978833,0.001044125,0.0006197199,0.00007276521,0.000178991,0.0002010613],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003535673,0.0005910359,0.7255571,0.0008338708,0.00009721478,0.001811561,0.05910737,0.0001557012,0.002691675,0.002212142,0.0007393867,0.2058494],"study_design_scores_gemma":[0.000009195096,0.0004630151,0.9116431,0.0005115016,0.00007387864,0.0004344674,0.0802731,0.0001059306,0.0005394559,0.0004897396,0.005443474,0.00001315436],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947043,0.001292877,0.0000826984,0.0003170419,0.000009841374,0.000008575764,0.00003623315,0.000001164422,0.003547302],"genre_scores_gemma":[0.9983417,0.000875565,0.00004690874,0.00004945109,0.000009504194,0.00001172225,0.0000186864,7.910625e-7,0.0006456159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9997598,"threshold_uncertainty_score":0.009382427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06130638748849182,"score_gpt":0.4155235502387062,"score_spread":0.3542171627502144,"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."}}