{"id":"W4399564582","doi":"10.1016/j.acalib.2024.102908","title":"What is ideal EDI learning for academic librarians? Discovering EDI learning stories through appreciative inquiry","year":2024,"lang":"en","type":"article","venue":"The Journal of Academic Librarianship","topic":"Library Science and Administration","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Concordia University; Canadian Association of Research Libraries","keywords":"Appreciative inquiry; Ideal (ethics); Mathematics education; Computer science; Pedagogy; Sociology; Psychology; Epistemology; Philosophy","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication","research_integrity"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.005506821,0.0002831192,0.000390947,0.0001905234,0.001644107,0.001537826,0.001514847,0.0005602,0.000150397],"category_scores_gemma":[0.001176943,0.0002022402,0.000255525,0.00074277,0.0007263564,0.03954806,0.0002087097,0.004033998,0.00002564058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000117336,"about_ca_system_score_gemma":0.001770396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006422698,"about_ca_topic_score_gemma":0.000004642038,"domain_scores_codex":[0.99582,0.0009884371,0.0009207969,0.0003367173,0.001059265,0.0008747683],"domain_scores_gemma":[0.9956338,0.003185779,0.0007000397,0.0001436138,0.00008195409,0.0002548297],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003141133,0.00001583571,0.006480075,0.0001182896,0.0001584722,0.00001706753,0.8189234,0.001352979,0.001109825,0.1206651,0.03639007,0.01445472],"study_design_scores_gemma":[0.0004195694,0.0004319001,0.0009548836,0.001312074,0.0001536675,0.00004761319,0.2636674,0.0008270519,0.002668804,0.09264101,0.6364358,0.0004402605],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5395465,0.0751075,0.04902282,0.2775133,0.03748447,0.0020301,0.00002840287,0.0008687724,0.01839806],"genre_scores_gemma":[0.9445605,0.02312169,0.0006274585,0.002139457,0.01754241,0.00001380251,0.00001045113,0.00006556477,0.01191871],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6000457,"threshold_uncertainty_score":0.9996556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1073707708303375,"score_gpt":0.379290619349631,"score_spread":0.2719198485192935,"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."}}