{"id":"W4413199842","doi":"10.3102/ip.25.2197288","title":"Centering Deep Care Among Newcomer Siblings-of-Color: Countering Hegemonic Frames of Doing Gender in Computing Education (Poster 24)","year":2025,"lang":"en","type":"article","venue":"","topic":"Gender and Technology in Education","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Hegemony; Computer science; Psychology; Multimedia; Political science; Law","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002668783,0.00009042799,0.0001718052,0.0004426815,0.0001563409,0.00002895275,0.0002384017,0.0001234416,0.00003741576],"category_scores_gemma":[0.00006572453,0.00009838859,0.00004850591,0.0005950571,0.0001529376,0.0001645897,0.00009289826,0.0001524568,0.000001504178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001933623,"about_ca_system_score_gemma":0.0003024918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004398236,"about_ca_topic_score_gemma":0.003882496,"domain_scores_codex":[0.9990211,0.00005921811,0.0003429978,0.0001973217,0.0001444191,0.0002349369],"domain_scores_gemma":[0.9994473,0.00007868897,0.0001303044,0.0001623155,0.0001556969,0.00002573657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.000005122552,0.00009937074,0.8776135,0.0002240416,0.00002330328,2.199203e-7,0.08798924,0.0002679015,0.0007335513,0.007165083,0.00004221387,0.02583649],"study_design_scores_gemma":[0.0004612815,0.00003280817,0.3881441,0.000580127,0.00003979641,9.720557e-7,0.5968459,0.000834373,0.007976179,0.003248989,0.001547657,0.0002877315],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9497606,0.0005308631,0.002238063,0.0002366803,0.00139784,0.0002401158,4.161548e-7,0.00005604635,0.04553942],"genre_scores_gemma":[0.9970179,0.00003771795,0.002665185,0.00008087706,0.00004383521,0.000009062268,0.000003108452,0.000006570884,0.0001357452],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5088567,"threshold_uncertainty_score":0.6648846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0170039942328675,"score_gpt":0.3371476883132433,"score_spread":0.3201436940803758,"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."}}