{"id":"W7162010877","doi":"10.82308/1706","title":"The bias of libraries: Montréal's Grande Bibliothèque","year":2014,"lang":"en","type":"dissertation","venue":"","topic":"Library Science and Administration","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transformative learning; Emerging technologies; Reproduction; Scale (ratio); Democracy; Digital media; Dissemination; New media; Cultural bias","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003001075,0.0003095167,0.0004161792,0.001810483,0.02747971,0.01678689,0.001809441,0.002132222,0.02073631],"category_scores_gemma":[0.009843064,0.0004322349,0.0002953474,0.005286018,0.0139253,0.005352209,0.006110079,0.002895627,0.001122666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1307372,"about_ca_system_score_gemma":0.1110942,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9679125,"about_ca_topic_score_gemma":0.9874659,"domain_scores_codex":[0.9958971,0.00108676,0.00006711094,0.0003643479,0.001508458,0.001076325],"domain_scores_gemma":[0.9936408,0.001535945,0.0005419285,0.0003348284,0.002146652,0.001799791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001643478,0.00007722555,0.01756928,0.0004353254,0.00004505931,0.002016782,0.2065413,0.0005880725,0.001327355,0.4036207,0.2573021,0.1103124],"study_design_scores_gemma":[0.00001976687,0.00002700299,0.01866206,0.0001908803,0.00001596139,0.0001375735,0.04498969,0.000128883,0.0002561347,0.003698925,0.9318019,0.00007123336],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2309341,0.01772439,0.001939323,0.2031079,0.002070671,0.0001732351,0.001180703,0.0004690737,0.5424007],"genre_scores_gemma":[0.8532662,0.003450298,0.000621276,0.01003963,0.0004135101,0.00005866779,0.0001541643,0.0002010308,0.1317953],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1307372,"threshold_uncertainty_score":0.948569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02948993513285642,"score_gpt":0.2937155884272631,"score_spread":0.2642256532944067,"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."}}