{"id":"W2171632631","doi":"10.18174/136242","title":"Can we learn our way to sustainable management? : adaptive collaborative management in Mafungautsi State Forest, Zimbabwe","year":2010,"lang":"en","type":"dissertation","venue":"","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centre for International Forestry Research; Nanomaterials Microdevices Research Center, Osaka Institute of Technology; Defence Research and Development Canada","keywords":"Natural resource management; Adaptive management; Natural resource; Resource management (computing); Ecosystem management; Citizen journalism; Participatory management; Sustainable management; Environmental resource management; Business; Participatory action research; Environmental planning; Political science; Economics; Geography; Sustainability; Computer science; Management; Economic growth; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007515935,0.0002715551,0.0001957262,0.0009679073,0.004754232,0.001761856,0.0008378644,0.0008483968,0.003059054],"category_scores_gemma":[0.001456811,0.0002409388,0.0001122258,0.001413185,0.002431055,0.001328091,0.00255331,0.0008249922,0.0001492735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004813792,"about_ca_system_score_gemma":0.00358743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1966967,"about_ca_topic_score_gemma":0.4007205,"domain_scores_codex":[0.9994387,0.0001955899,0.00001682312,0.00005414444,0.00005124641,0.0002435228],"domain_scores_gemma":[0.9997419,0.00008278836,0.00004936829,0.00001180232,0.0000285062,0.00008567415],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0004882064,0.001055892,0.1580273,0.001744241,0.0001301586,0.02192472,0.4303391,0.001981203,0.02369522,0.03150656,0.01059424,0.3185132],"study_design_scores_gemma":[0.0001626104,0.0006931181,0.5411652,0.001078965,0.0001180502,0.001832225,0.3408962,0.003217875,0.001688039,0.006968716,0.1020811,0.00009802364],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9832482,0.001903538,0.0006966799,0.004889598,0.00002185536,0.0002772174,0.00007614701,0.00001522631,0.008871595],"genre_scores_gemma":[0.9947492,0.0009314751,0.000973139,0.0002220431,0.000004641946,0.0001221665,0.00004801126,0.00000308614,0.002946247],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1966967,"threshold_uncertainty_score":0.3911034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05210143287840176,"score_gpt":0.372848339051401,"score_spread":0.3207469061729992,"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."}}