<|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:"Demographic and Economic Changes in Remote Australia."
Abstract:"Varied distribution of resources, populations and Indigenous people result in significant socio-economic differences among statistical local areas (SLAs) in remote Australia. These differences indicate that the experience of change at the height of the resources boom will differ among SLAs in the region. Using hierarchical cluster analysis with Ward's minimum variance method, four socio-economic clusters were identified among the 197 SLAs in the region. The first was the most disadvantaged, with limited resources and human capital and the highest percentage of Indigenous people. The other three clusters improved in sequence, with the fourth having the most resources with the highest employment rate and income but least number of Indigenous people. Multivariate analysis of variance with main and interaction effects showed changes in demographics, industry structure, human capital and income over the period of investigation for the region as a whole and differences in the extent of these changes among the clusters. Policy interventions in the region are suggested for each group to match its specific needs.."
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: 

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Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [0];
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Demographic and Economic Changes in Remote Australia
Varied distribution of resources, populations and Indigenous people result in significant socio-economic differences among statistical local areas (SLAs) in remote Australia. These differences indicate that the experience of change at the height of the resources boom will differ among SLAs in the region. Using hierarchical cluster analysis with Ward's minimum variance method, four socio-economic clusters were identified among the 197 SLAs in the region. The first was the most disadvantaged, with limited resources and human capital and the highest percentage of Indigenous people. The other three clusters improved in sequence, with the fourth having the most resources with the highest employment rate and income but least number of Indigenous people. Multivariate analysis of variance with main and interaction effects showed changes in demographics, industry structure, human capital and income over the period of investigation for the region as a whole and differences in the extent of these changes among the clusters. Policy interventions in the region are suggested for each group to match its specific needs.