<|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:"Modelling locational choices of older adults in China, 2010-2015."
Abstract:"Using the microdata samples of the 2015 1% national population sample survey, this study makes the first attempt to investigate the extent to which regional attributes and personal characteristics jointly affect older adults' choices among the 30 provinces of mainland China. Results from the binary logit model indicated that older adults' decisions of whether to move were affected by their demographic characteristics, socio-economic status, and health status, while provinces with a lower cost of living, poorer natural and man-made amenities, and a larger outflow of children had a higher propensity of older out-migration. Results from the conditional logit models indicated that the cost of living, medical services, public green areas, temperature difference, the location of grandchildren, and migration distance played a significant role in affecting older adults' choices of where to move. The effect of provincial factors on the decisions of where to move turned out to vary by individuals' age, socio-economic status, and urban-rural division of destination. This paper enriches our knowledge about older migration in China by delving into the heterogeneity in older people's locational choices and by investigating migration drivers related to family and amenities.."
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 = [7];
Q3 = [];
Q4 = [0];
Q5 = [1];
Q6 = [1].
Modelling locational choices of older adults in China, 2010-2015
Using the microdata samples of the 2015 1% national population sample survey, this study makes the first attempt to investigate the extent to which regional attributes and personal characteristics jointly affect older adults' choices among the 30 provinces of mainland China. Results from the binary logit model indicated that older adults' decisions of whether to move were affected by their demographic characteristics, socio-economic status, and health status, while provinces with a lower cost of living, poorer natural and man-made amenities, and a larger outflow of children had a higher propensity of older out-migration. Results from the conditional logit models indicated that the cost of living, medical services, public green areas, temperature difference, the location of grandchildren, and migration distance played a significant role in affecting older adults' choices of where to move. The effect of provincial factors on the decisions of where to move turned out to vary by individuals' age, socio-economic status, and urban-rural division of destination. This paper enriches our knowledge about older migration in China by delving into the heterogeneity in older people's locational choices and by investigating migration drivers related to family and amenities.