<|begin_of_text|><|start_header_id|>system<|end_header_id|>You are an expert on climate change, human mobility and migration. Answer the question truthfully.<|eot_id|><|start_header_id|>user<|end_header_id|>Here are the title and abstract of a scientific paper probably related to climate change, human mobility and migration..
Title:"The price of certainty: How the politics of pandemic data demand an ethics of care."
Abstract:"The Covid-19 pandemic broke on a world whose grip on epistemic trust was already in disarray. The first months of the pandemic saw many governments publicly performing reliance on epidemiological and modelling expertise in order to signal that data would be the basis for justifying whatever population-level measures of control were judged necessary. But comprehensive data has not become available, and instead scientists, policymakers and the public find themselves in a situation where policy inputs determine the data available and vice versa. This essay asks how we can live with what Amoore has termed 'post-Cartesian doubt' in situations of existential risk, and what kind of approach to science and data can answer the moral and human demands of a situation such as the Covid-19 pandemic. I suggest that science and policy could be able to control the pandemic better by addressing the sources of uncertainty and missing data not as gaps in the information landscape, but as individuals who are likely to be members of less-visible and less powerful groups including low-wage workers, the elderly, migrants, prisoners and others. This would shift both data use and policy toward an ethics of care, an embodied approach which asks what people need and how they behave in relation to each other, rather than how to manage population-level behaviour. This approach, I argue, is more appropriate for pandemic response than a utilitarian calculation of how many people each country should expect to lose as a result of the disease.."
I have six questions you need to answer.
Q1: Is this article is about 'human migration mobility': 1 = yes; 0 = no. Answer with a number. Do not give a textual explanation.

Q2: What drivers of migration and mobility does the article study? 0 = 'other', 1 = 'climate', 2 = 'environment', 3 = 'economic', 4 = 'conflict', 5 = 'political', 6 = 'social', 7 = 'family'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q3: What is the overall sentiment of the article?:0 = 'neutral', 1 = 'negative', 2 = 'positive'. Answer with a number. Do not give a textual explanation.

Q4: What type of climate or environmental keywords are explicitly mentioned?:  0 = 'none', 1 = 'algal blooms', 2 = 'infestation', 3 = 'infectious diseases', 4 = 'ocean acidification', 5 = 'sea ice', 6 = 'acid rain', 7 = 'drought', 8 = 'cold wave', 9 = 'heat wave', 10 = 'glacial', 11 = 'wildfire', 12 = 'air pollution', 13 = 'biodiversity loss', 14 = 'coastal erosion', 15 = 'land degradation', 16 = 'deforestation', 17 = 'desertification', 18 = 'water pollution', 19 = 'diebacks', 20 = 'permafrost loss', 21 = 'sand mining', 22 = 'sea level rise', 23 = 'earthquake', 24 = 'tsunami', 25 = 'volcanic', 26 = 'flood', 27 = 'avalanche', 28 = 'landslide', 29 = 'downburst', 30 = 'thunderstorm', 31 = 'sandstorm', 32 = 'haze', 33 = 'storm', 34 = 'cyclone', 35 = 'blizzard', 36 = 'hail', 37 = 'snow', 38 = 'tornado', 39 = 'wind', 40 = 'hurricane', 41 = 'typhoon', 42 = 'other'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q5: What discipline does the article belong to?: 0 = 'other', 1 = 'social science', 2 = 'natural science', 3 = 'arts and humanities', 4 = 'multidiscipline and interdiscipline'. Answer with a number. Do not give a textual explanation.

Q6: Does the article apply quantitative and/or statistical analysis?: 0 = 'no', 1 = 'yes'. Answer with a number. Do not give a textual explanation.

Use the following template: 

Q1 = [];
Q2 = [];
Q3 = [];
Q4 = [];
Q5 = [];
Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [1];
Q2 = [];
Q3 = [];
Q4 = [];
Q5 = [1];
Q6 = [0].
The price of certainty: How the politics of pandemic data demand an ethics of care
The Covid-19 pandemic broke on a world whose grip on epistemic trust was already in disarray. The first months of the pandemic saw many governments publicly performing reliance on epidemiological and modelling expertise in order to signal that data would be the basis for justifying whatever population-level measures of control were judged necessary. But comprehensive data has not become available, and instead scientists, policymakers and the public find themselves in a situation where policy inputs determine the data available and vice versa. This essay asks how we can live with what Amoore has termed 'post-Cartesian doubt' in situations of existential risk, and what kind of approach to science and data can answer the moral and human demands of a situation such as the Covid-19 pandemic. I suggest that science and policy could be able to control the pandemic better by addressing the sources of uncertainty and missing data not as gaps in the information landscape, but as individuals who are likely to be members of less-visible and less powerful groups including low-wage workers, the elderly, migrants, prisoners and others. This would shift both data use and policy toward an ethics of care, an embodied approach which asks what people need and how they behave in relation to each other, rather than how to manage population-level behaviour. This approach, I argue, is more appropriate for pandemic response than a utilitarian calculation of how many people each country should expect to lose as a result of the disease.