<|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:"Non-parametric frontier estimation of health care efficiency among US states, 2002-2008."
Abstract:"This paper examines cross-state health care efficiency rankings using modern non-parametric estimators. Cross-state efficiency rankings are robust to minor modifications in the input-output combinations used for estimation. This paper finds that there is no clear relationship between health care efficiency rankings and per capita health care expenditures in that state in the models used for this paper, even though this is a key variable that policymakers target. It also finds that Massachusetts, in one dataset, has shown significant productivity improvement from 2005 to 2008, the time period during which its health care reform was launched. In a second dataset, from 2002 to 2007, productivity regressed in Massachusetts. This may hint that efficiency gains from structural health care reform can outweigh population behavioral inefficiencies from using the ER as a source of primary care with insurance coverage expansion. I also find that states that chose to expand Medicaid were less efficient, on average, than states that did not choose to expand Medicaid. Simple variable comparisons suggest that this is an artifact of the data and political decision making, rather than people migrating for Medicaid or productive inefficiency.."
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 = [];
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Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [0];
Q2 = [];
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Q4 = [];
Q5 = [0];
Q6 = [1].
Non-parametric frontier estimation of health care efficiency among US states, 2002-2008
This paper examines cross-state health care efficiency rankings using modern non-parametric estimators. Cross-state efficiency rankings are robust to minor modifications in the input-output combinations used for estimation. This paper finds that there is no clear relationship between health care efficiency rankings and per capita health care expenditures in that state in the models used for this paper, even though this is a key variable that policymakers target. It also finds that Massachusetts, in one dataset, has shown significant productivity improvement from 2005 to 2008, the time period during which its health care reform was launched. In a second dataset, from 2002 to 2007, productivity regressed in Massachusetts. This may hint that efficiency gains from structural health care reform can outweigh population behavioral inefficiencies from using the ER as a source of primary care with insurance coverage expansion. I also find that states that chose to expand Medicaid were less efficient, on average, than states that did not choose to expand Medicaid. Simple variable comparisons suggest that this is an artifact of the data and political decision making, rather than people migrating for Medicaid or productive inefficiency.