{"id":"W3196650961","doi":"10.1080/01436597.2021.1965871","title":"Land appropriation, customary tenure and rural livelihoods: gold mining in Ghana","year":2021,"lang":"en","type":"article","venue":"Third World Quarterly","topic":"Agriculture, Land Use, Rural Development","field":"Agricultural and Biological Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Livelihood; Agrarian society; Customary land; Appropriation; Land tenure; Expropriation; Land grabbing; Politics; Economic growth; Gold mining; Corporate governance; Political science; State (computer science); Development economics; Geography; Business; Agriculture; Economics; Law","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000669156,0.0001047476,0.0001200236,0.0003406998,0.001172957,0.0007097695,0.0001917481,0.0003199741,0.001680234],"category_scores_gemma":[0.0009780024,0.00008044729,0.00003966007,0.0009566497,0.002525725,0.0009715108,0.001125933,0.00031094,0.00006544323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001453515,"about_ca_system_score_gemma":0.0007967011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01616945,"about_ca_topic_score_gemma":0.05772732,"domain_scores_codex":[0.9997128,0.0001726551,0.00001285745,0.00001727764,0.00002284317,0.00006148856],"domain_scores_gemma":[0.9992169,0.0002982871,0.0003507348,0.00001715825,0.00003392836,0.00008298631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001235847,0.0001655926,0.4608284,0.0005462274,0.0000141468,0.006100521,0.468784,0.0001705097,0.004096556,0.005457921,0.0008557629,0.05285692],"study_design_scores_gemma":[0.00001480637,0.0001015585,0.4132372,0.0002306951,0.00001087213,0.001466347,0.5700023,0.0001106888,0.000490005,0.001326993,0.01299896,0.000009640635],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971318,0.0007251585,0.00003376637,0.0005081422,0.000002144229,0.000003303997,0.000006920495,4.864839e-7,0.001588312],"genre_scores_gemma":[0.9991289,0.0005017727,0.00003869081,0.00003254268,0.000001283457,0.000002195159,0.000004312658,4.67574e-7,0.0002898443],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01616945,"threshold_uncertainty_score":0.03215069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008439799666583207,"score_gpt":0.1931465703653182,"score_spread":0.184706770698735,"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."}}