{"id":"W2766951477","doi":"10.1111/gec3.12350","title":"Re‐working mobilities: Emergent geographies of employment‐related mobility","year":2017,"lang":"en","type":"article","venue":"Geography Compass","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trinity College; Memorial University of Newfoundland; University of Alberta","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Mobilities; Sociology; Politics; Work (physics); Journey to work; Phenomenology (philosophy); Economic geography; Social mobility; Gender studies; Social science; Political science; Geography; Epistemology; Public transport","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009825802,0.0002094689,0.0002132008,0.004101703,0.001884115,0.004421024,0.0005344353,0.0007130947,0.005432765],"category_scores_gemma":[0.003381717,0.0001525434,0.0002662846,0.005469433,0.007187078,0.005392229,0.004200795,0.000752754,0.0003081773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001510694,"about_ca_system_score_gemma":0.0007809745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00507076,"about_ca_topic_score_gemma":0.006345849,"domain_scores_codex":[0.9994685,0.0002845111,0.00002513558,0.00008340475,0.00006816347,0.00007030314],"domain_scores_gemma":[0.99824,0.0009631547,0.0002926272,0.000253728,0.0001372835,0.0001132203],"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":[0.00006458779,0.00002267156,0.0400949,0.0004417434,0.00003778609,0.001010233,0.3539393,0.001878723,0.001248012,0.539572,0.006285613,0.05540455],"study_design_scores_gemma":[0.00001126944,0.00003747521,0.06902843,0.0006298638,0.00002944921,0.001024166,0.5158418,0.002523793,0.0004572713,0.2295848,0.1807766,0.00005511299],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.802546,0.004178342,0.04702053,0.01085587,0.0002352442,0.0001190007,0.001399121,0.0002133271,0.1334325],"genre_scores_gemma":[0.9943329,0.001040202,0.002436781,0.00009711489,0.00004664012,0.00003790712,0.0001991821,0.00002796178,0.001781348],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005432765,"threshold_uncertainty_score":0.01817435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03502986477698249,"score_gpt":0.3096762136100331,"score_spread":0.2746463488330506,"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."}}