{"id":"W2058931236","doi":"10.1016/j.geoforum.2009.10.006","title":"Labouring geography: Negotiating scales, strategies and future directions","year":2009,"lang":"en","type":"article","venue":"Geoforum","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":60,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Agency (philosophy); Negotiation; Sociology; Human geography; Construct (python library); Normative; Politics; Field (mathematics); Scale (ratio); Critical geography; Time geography; Cultural geography; Economic geography; Political economy; Political science; Social science; Historical geography; Economics; Geography; Law; Development geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0002862621,0.000125865,0.0001528232,0.00008531139,0.003297894,0.00003905057,0.00005690876,0.00009377037,0.00004699143],"category_scores_gemma":[0.00001334367,0.0001053263,0.00003719918,0.0001544399,0.00003828001,0.0002635628,0.0001108388,0.0002995871,0.00002026943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001796217,"about_ca_system_score_gemma":0.00003104359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003102235,"about_ca_topic_score_gemma":0.0003394344,"domain_scores_codex":[0.9985288,0.00006774357,0.0002085462,0.0001776548,0.0001039831,0.0009132197],"domain_scores_gemma":[0.9996027,0.00006740458,0.00007585247,0.0001239542,0.00006133621,0.00006880092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002186262,0.00005100705,0.7547282,0.00009640121,0.00006725582,0.000005581651,0.004320137,0.00001032471,0.00007948767,0.1526911,0.009957498,0.07797119],"study_design_scores_gemma":[0.000225709,0.00004557708,0.7584985,0.00004546148,0.00001099367,7.944711e-7,0.01894266,0.000009164894,0.000001285405,0.003849134,0.218263,0.0001075964],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8700171,0.0111933,0.0001058284,0.03303015,0.001413433,0.0004707426,0.00001909081,0.0004627565,0.08328758],"genre_scores_gemma":[0.9938251,0.002427395,0.0001939519,0.001128924,0.001168221,0.00003518332,0.00001201439,0.00001255727,0.001196654],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2083056,"threshold_uncertainty_score":0.9979997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01871806998460191,"score_gpt":0.3417254131261666,"score_spread":0.3230073431415647,"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."}}