{"id":"W2746940567","doi":"10.1111/cag.12397","title":"Operating anew: Queering GIS with good enough software","year":2017,"lang":"en","type":"article","venue":"Canadian Geographies / Géographies canadiennes","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trinity College","funders":"Bowdoin College","keywords":"Queer; Status quo; Politics; Sociology; Elite; Geographic information system; Field (mathematics); Gender studies; Political science; Geography; Law; Cartography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.05478531,0.0009890844,0.0005858548,0.003738484,0.01163977,0.02401718,0.003424302,0.004219635,0.01400645],"category_scores_gemma":[0.1302398,0.001274058,0.0008470776,0.002944981,0.04146929,0.03681063,0.01192783,0.009518843,0.00425614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007843634,"about_ca_system_score_gemma":0.01490438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02281578,"about_ca_topic_score_gemma":0.02954116,"domain_scores_codex":[0.9605172,0.02562018,0.001265213,0.002912825,0.008116758,0.001567723],"domain_scores_gemma":[0.8785735,0.07717799,0.003562109,0.02140633,0.01410965,0.00517047],"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":[0.00009874249,0.00007896905,0.002807093,0.0001840279,0.00002353103,0.0005736189,0.1770452,0.001258865,0.002596116,0.6176662,0.06817836,0.1294894],"study_design_scores_gemma":[0.00002728849,0.00005126967,0.00047367,0.0004062475,0.00002036012,0.000362304,0.02970133,0.002849068,0.002167191,0.2522939,0.711562,0.00008539279],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03795214,0.002988755,0.6157951,0.1782056,0.002487594,0.0002745175,0.0003151717,0.008288881,0.1536923],"genre_scores_gemma":[0.4776735,0.003915581,0.4058932,0.02287859,0.001009404,0.0004373092,0.0005859493,0.01396837,0.07363803],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9883602,"threshold_uncertainty_score":0.2897359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01296089002493622,"score_gpt":0.2266649091497937,"score_spread":0.2137040191248575,"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."}}