{"id":"W4200018149","doi":"10.1080/17442222.2021.2015140","title":"White animals: racializing sheep and beavers in the Argentinian Tierra del Fuego","year":2021,"lang":"en","type":"article","venue":"Latin American and Caribbean Ethnic Studies","topic":"Geographies of human-animal interactions","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"White (mutation); Racialization; Anthropocentrism; Ethnology; CITES; Dominion; Poaching; State (computer science); Appropriation; Power (physics); Creole language; Exceptionalism; Geography; Sociology; Political science; Race (biology); Gender studies; Archaeology; Law; Politics; Wildlife; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005625332,0.0001458998,0.0002923169,0.0001019086,0.0007309015,0.00008894032,0.0001400565,0.00003514881,0.00005952704],"category_scores_gemma":[0.000493451,0.0001225744,0.00007308288,0.0007808832,0.001626033,0.0001099325,0.0001059556,0.0002436146,0.000003976192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003202134,"about_ca_system_score_gemma":0.00003923721,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002778487,"about_ca_topic_score_gemma":0.09780842,"domain_scores_codex":[0.9984704,0.0003716889,0.0002292282,0.0003121075,0.0002633681,0.0003532126],"domain_scores_gemma":[0.9991,0.0004387301,0.0001249938,0.0001522856,0.0001141921,0.00006984432],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00003133233,0.0001014402,0.2622048,0.00003732389,0.0003325077,0.00006554255,0.6844677,0.000004804866,0.0001898074,0.0143556,0.004750908,0.03345823],"study_design_scores_gemma":[0.0001014754,0.00004307672,0.3950527,0.00001986048,0.0000374025,0.000002166631,0.5980428,0.000005573831,0.000003468839,0.0004630514,0.006115803,0.0001126571],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9416239,0.01781323,0.000002136718,0.00769011,0.0002229619,0.0001814514,0.00001191501,0.00004724622,0.03240702],"genre_scores_gemma":[0.9885449,0.00952941,0.0003791278,0.0009086708,0.0001212479,0.00002608572,0.000002037094,0.000009708879,0.0004788061],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1328478,"threshold_uncertainty_score":0.9186542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09014308956447555,"score_gpt":0.3931861405383597,"score_spread":0.3030430509738842,"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."}}