{"id":"W2781502534","doi":"10.1016/j.cities.2017.12.018","title":"Do-it-yourself (DIY) adaptation: Civic initiatives as drivers to address climate change at the urban scale","year":2018,"lang":"en","type":"article","venue":"Cities","topic":"Sustainability and Climate Change Governance","field":"Environmental Science","cited_by":80,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"Fonds de Recherche du Québec - Santé","keywords":"Corporate governance; Civil society; Scale (ratio); Political science; Climate change; Civic engagement; Work (physics); Adaptation (eye); Collective action; Climate change adaptation; Environmental planning; Public administration; Sociology; Geography; Business; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002842166,0.0002764171,0.0001868054,0.000644695,0.004094293,0.006164953,0.0008595265,0.001766843,0.01339021],"category_scores_gemma":[0.004791568,0.0002052189,0.0003142099,0.001126586,0.004128518,0.004563243,0.007140054,0.002678465,0.001283955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002076468,"about_ca_system_score_gemma":0.004977995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003853946,"about_ca_topic_score_gemma":0.0155805,"domain_scores_codex":[0.9986059,0.0008409917,0.0000204597,0.0001164026,0.0001427606,0.0002735145],"domain_scores_gemma":[0.9963109,0.0005381912,0.0003867294,0.0003452418,0.000312197,0.002106728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002078205,0.002233057,0.136992,0.0003974162,0.00009986531,0.0004925432,0.04888968,0.00117826,0.001675121,0.317015,0.08473545,0.4060839],"study_design_scores_gemma":[0.0001217183,0.0004055928,0.1343521,0.0005312422,0.0001080642,0.0003608225,0.1943568,0.003854533,0.002229564,0.1388469,0.5247092,0.0001233108],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3986677,0.001475163,0.00835383,0.122578,0.001375039,0.0001927979,0.0001895681,0.0003161751,0.4668518],"genre_scores_gemma":[0.9837331,0.0005670756,0.00171883,0.002700556,0.00009716807,0.00006811104,0.0000511417,0.00004636759,0.01101766],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01339021,"threshold_uncertainty_score":0.04479474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04509836101230572,"score_gpt":0.2770205429745641,"score_spread":0.2319221819622584,"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."}}