{"id":"W2398212633","doi":"10.1177/0308518x16649184","title":"Putting mobility theory to work: Conceptualizing employment-related geographical mobility","year":2016,"lang":"en","type":"article","venue":"Environment and Planning A Economy and Space","topic":"Migration, Aging, and Tourism Studies","field":"Social Sciences","cited_by":102,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; University of Alberta","funders":"","keywords":"Work (physics); Mobilities; Economic geography; Sociology; Politics; Geographic mobility; Bridge (graph theory); Conceptual framework; Regional science; Geography; Political science; Social science; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.001227619,0.0001248449,0.0001690784,0.00004148591,0.0006779477,0.00005706093,0.00006295768,0.00007742036,0.0001945595],"category_scores_gemma":[0.00008251244,0.00009699661,0.0000354881,0.0000533243,0.000429222,0.000153277,0.00007088672,0.00007658613,0.00001362192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003624904,"about_ca_system_score_gemma":0.00001102095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004155839,"about_ca_topic_score_gemma":0.00009799974,"domain_scores_codex":[0.9989173,0.0001904258,0.0001761142,0.0003531858,0.00008130677,0.0002817069],"domain_scores_gemma":[0.9992157,0.000435415,0.00006633317,0.0001126856,0.000006056801,0.0001637989],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002570884,0.00003450329,0.8262027,0.000005220309,0.00004572552,0.000001847212,0.1526158,0.00001790277,0.00001450169,0.0101546,0.000468336,0.01041318],"study_design_scores_gemma":[0.0006688559,0.00008908904,0.7495884,0.000111321,0.0000427613,9.165991e-7,0.01044046,0.00001605333,0.00004975799,0.0210567,0.2175248,0.0004108227],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926776,0.001328063,0.001366319,0.002198525,0.00006707398,0.0002374354,0.000003544826,0.0000465945,0.002074871],"genre_scores_gemma":[0.99729,0.000351202,0.0003438102,0.0001243276,0.00009489123,0.00002622981,0.000001279317,0.000005592738,0.001762663],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2170565,"threshold_uncertainty_score":0.5214294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01492016645412567,"score_gpt":0.2460488432225481,"score_spread":0.2311286767684225,"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."}}