{"id":"W4391963371","doi":"10.18260/1-2--37673","title":"Resilience and Innovation in Response to COVID-19: Learnings from Northeast Academic Makerspaces","year":2024,"lang":"en","type":"article","venue":"2021 ASEE Virtual Annual Conference Content Access Proceedings","topic":"Teaching and Learning Programming","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Experiential learning; Engineering education; Higher education; Curriculum; Pandemic; Engineering; Sociology; Pedagogy; Political science; Engineering management; Medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.01130537,0.0005317567,0.0005278866,0.001594376,0.01851765,0.01428257,0.002524954,0.002841529,0.006425359],"category_scores_gemma":[0.0116518,0.0003564274,0.0005640102,0.001476283,0.01896955,0.007432076,0.02721387,0.004962919,0.0007051365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01191327,"about_ca_system_score_gemma":0.01157772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0148601,"about_ca_topic_score_gemma":0.03881975,"domain_scores_codex":[0.9934528,0.002797539,0.0001439632,0.000611829,0.001278925,0.00171498],"domain_scores_gemma":[0.987969,0.003061986,0.001202133,0.001111503,0.00139115,0.00526415],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001287975,0.0003069139,0.02970376,0.00009521675,0.00002225531,0.001769279,0.8964156,0.0006262129,0.001159144,0.02602434,0.007917587,0.03583076],"study_design_scores_gemma":[0.000006462014,0.0001214917,0.01179607,0.000120142,0.000008526704,0.0001651034,0.9362562,0.0004550708,0.0006984256,0.006641449,0.04368008,0.00005102418],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9635871,0.0003061777,0.001536691,0.01158933,0.0001994524,0.00003341536,0.00004616573,0.0000622548,0.02263939],"genre_scores_gemma":[0.9965564,0.0001301329,0.0003596988,0.0007019888,0.00001581356,0.00001593099,0.00002048684,0.00002024743,0.002179384],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01851765,"threshold_uncertainty_score":0.08643723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06981795966438196,"score_gpt":0.3414601149451684,"score_spread":0.2716421552807864,"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."}}