{"id":"W4390538994","doi":"10.3390/educsci14010057","title":"Deconstructing the Normalization of Data Colonialism in Educational Technology","year":2024,"lang":"en","type":"article","venue":"Education Sciences","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Colonialism; Ideology; Normalization (sociology); Analytics; Data science; Sociology; Field (mathematics); Big data; Learning analytics; Computer science; Social science; Engineering ethics; Politics; Political science; Law; Engineering; Data mining","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":[0.06012007,0.0004274166,0.0007860988,0.01002276,0.007200742,0.02058959,0.001843783,0.001984967,0.001458022],"category_scores_gemma":[0.09572049,0.0006455905,0.0007048657,0.007897904,0.06796638,0.02837169,0.01238755,0.006297477,0.0001825942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009166651,"about_ca_system_score_gemma":0.01321991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006604709,"about_ca_topic_score_gemma":0.01129871,"domain_scores_codex":[0.9535664,0.03228592,0.003528811,0.002996391,0.005901846,0.00172074],"domain_scores_gemma":[0.8014084,0.1485868,0.01565274,0.02011865,0.01232288,0.001910535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002511048,0.00002018065,0.006579947,0.0003814741,0.00002186214,0.0004046949,0.1684109,0.0002922667,0.0005547906,0.7908939,0.0007956295,0.03161929],"study_design_scores_gemma":[0.0000216793,0.00006885225,0.01326578,0.004498043,0.00007312033,0.00150295,0.2460934,0.00277004,0.003783302,0.520299,0.2075278,0.000096076],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4907045,0.02788863,0.1852142,0.1037793,0.001221877,0.0003453052,0.0001866906,0.0001490098,0.1905105],"genre_scores_gemma":[0.9783477,0.003159304,0.01431662,0.002321544,0.0001780513,0.00008500403,0.00003379743,0.00008098419,0.001477074],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9927993,"threshold_uncertainty_score":0.3179491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04586872087188163,"score_gpt":0.3974747660524453,"score_spread":0.3516060451805637,"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."}}