<|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:"Projections of Older Immigrants in France, 2008-2028."
Abstract:"Projections of elderly international migrants in France can provide data for social and health services to serve culturally and linguistically diverse elderly populations. In this regard, projections of future demographic trends are more useful than consideration of current migrant age structures, as the latter are biased. Often, immigrant children born in a host country are not counted with their parents for a variety of reasons. The paper evaluates the nature of return migration flows by older migrants. Although the volume of movement is lower than at younger working ages, immigration to France at older ages is significant and is made up mostly of women. However, the main component influencing trends in elderly migrants is age structure, which varies according to origin and migration history; were moves pre-independence or post-independence in relation to the country of origin: did they occur during an economic boom or bust; and how were they timed in relation to the policy environment? The paper shows how France's closed-border' policy from 1975 onwards and subsequent family reunification impacted on migration trends of older people by sex. Looking to the future, the migrant communities of longest standing will increase slightly. Exceptions include the Italians and Spanish who will decline in size. Those who arrived later - Moroccans, Turks, and others' - will increase more than twofold, and sub-Saharan Africans up to sixfold. The numbers of women will increase more rapidly than men. Copyright (c) 2016 John Wiley & Sons, Ltd.."
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 = [3,5,6,7];
Q3 = [];
Q4 = [0];
Q5 = [1];
Q6 = [1].
Projections of Older Immigrants in France, 2008-2028
Projections of elderly international migrants in France can provide data for social and health services to serve culturally and linguistically diverse elderly populations. In this regard, projections of future demographic trends are more useful than consideration of current migrant age structures, as the latter are biased. Often, immigrant children born in a host country are not counted with their parents for a variety of reasons. The paper evaluates the nature of return migration flows by older migrants. Although the volume of movement is lower than at younger working ages, immigration to France at older ages is significant and is made up mostly of women. However, the main component influencing trends in elderly migrants is age structure, which varies according to origin and migration history; were moves pre-independence or post-independence in relation to the country of origin: did they occur during an economic boom or bust; and how were they timed in relation to the policy environment? The paper shows how France's closed-border' policy from 1975 onwards and subsequent family reunification impacted on migration trends of older people by sex. Looking to the future, the migrant communities of longest standing will increase slightly. Exceptions include the Italians and Spanish who will decline in size. Those who arrived later - Moroccans, Turks, and others' - will increase more than twofold, and sub-Saharan Africans up to sixfold. The numbers of women will increase more rapidly than men. Copyright (c) 2016 John Wiley & Sons, Ltd.