<|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:"First catch your corpus: methodological challenges in constructing a thematic corpus."
Abstract:"This paper describes the process by which we have constructed a corpus of heterogeneous texts about non-human animals. It aims to contribute both methodologically - with respect to the challenges of compiling a thematic corpus - and substantively - in relation to the identification of some features of discourse about animals. Having introduced the research project and its guiding questions, the paper describes the principles of data selection and the procedures used in the analysis. We highlight the methods we devised both to avoid the potential circularity associated with pre-determined search terms, and to overcome the limitations of a relatively small corpus containing a wide range of relevant vocabulary. We go on to report some initial findings on the most frequent animal naming terms and adjectives describing them, including a small case study of the adjectives live and dead. The paper concludes by indicating the ways in which the iterative methods we have employed are open to further extension, and points to some methodological and substantive implications of this enterprise.."
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 = [];
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Q5 = [];
Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [0];
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Q6 = [0].
First catch your corpus: methodological challenges in constructing a thematic corpus
This paper describes the process by which we have constructed a corpus of heterogeneous texts about non-human animals. It aims to contribute both methodologically - with respect to the challenges of compiling a thematic corpus - and substantively - in relation to the identification of some features of discourse about animals. Having introduced the research project and its guiding questions, the paper describes the principles of data selection and the procedures used in the analysis. We highlight the methods we devised both to avoid the potential circularity associated with pre-determined search terms, and to overcome the limitations of a relatively small corpus containing a wide range of relevant vocabulary. We go on to report some initial findings on the most frequent animal naming terms and adjectives describing them, including a small case study of the adjectives live and dead. The paper concludes by indicating the ways in which the iterative methods we have employed are open to further extension, and points to some methodological and substantive implications of this enterprise.