<|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:"Family, school, neighbourhood or all three: Differences in tertiary educational achievement among the Russian ethno-linguistic minority in Tallinn Urban Region, Estonia."
Abstract:"Labour market outcomes of ethnic minorities tend to be lower compared to members of the majority population. Better education obtained in the host country has the potential to mitigate such ethnic labour market disadvantage. In this study, we will focus on the role of family, neighbourhood and school characteristics in the achievement of tertiary education among the minority population. Our empirical context is the capital city of Estonia, Tallinn, and its wider urban region. Tallinn Urban Region makes for an interesting case because of the high share of the minority population, modest immigration over the past three decades, and high levels segregation in different life domains, in neighbourhoods, schools and in the labour market. We apply a longitudinal study design to examine the factors that are related to the achievement of tertiary education among second and third generation immigrants. We find that studying in schools together with majority population students is associated with obtaining a university degree, when controlling for parental characteristics. However, levels of ethnic segregation in the childhood neighbourhood are not related to achieving tertiary education, but living in a neighbourhood with a higher share of tertiary-educated people is. Also, a higher level of social integration among minority children, but not immigrant generation, is positively associated with achieving tertiary education.."
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 = [2];
Q4 = [0];
Q5 = [1];
Q6 = [1].
Family, school, neighbourhood or all three: Differences in tertiary educational achievement among the Russian ethno-linguistic minority in Tallinn Urban Region, Estonia
Labour market outcomes of ethnic minorities tend to be lower compared to members of the majority population. Better education obtained in the host country has the potential to mitigate such ethnic labour market disadvantage. In this study, we will focus on the role of family, neighbourhood and school characteristics in the achievement of tertiary education among the minority population. Our empirical context is the capital city of Estonia, Tallinn, and its wider urban region. Tallinn Urban Region makes for an interesting case because of the high share of the minority population, modest immigration over the past three decades, and high levels segregation in different life domains, in neighbourhoods, schools and in the labour market. We apply a longitudinal study design to examine the factors that are related to the achievement of tertiary education among second and third generation immigrants. We find that studying in schools together with majority population students is associated with obtaining a university degree, when controlling for parental characteristics. However, levels of ethnic segregation in the childhood neighbourhood are not related to achieving tertiary education, but living in a neighbourhood with a higher share of tertiary-educated people is. Also, a higher level of social integration among minority children, but not immigrant generation, is positively associated with achieving tertiary education.